PREFIX dblp: <https://dblp.org/rdf/schema#>
SELECT ?authorName WHERE {
  <https://dblp.org/rec/conf/icapr/WangL05> dblp:authoredBy ?author .
  ?author dblp:creatorName ?authorName .
  FILTER ( ?authorName = "Graham Leedham" || ?authorName = "Lingyu Wang" )
}

Got 2 rows and 1 column:
| authorName     |
| -------------- |
| Graham Leedham |
| Lingyu Wang    |

Yes, Leedham, Graham and Wang, Lingyu co-authored the paper 'A Thermal Hand Vein Pattern Verification System'.

Did Leedham, Graham and Wang, Lingyu co-author the paper 'A Thermal Hand Vein Pattern Verification System'?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
dblp at https://qlever.cs.uni-freiburg.de/api/dblp with notes:
1. Use dblp:authoredBy to link publications to authors. The inverse (author -> pubs) is not via dblp:author; queries with dblp:author typically return no results.
2. Publication year is dblp:yearOfPublication (xsd:gYear). Avoid dblp:year. For last N years use YEAR(NOW()) in FILTER; use >= for inclusive bounds. Don’t assume current year in prose. MIN/MAX work on gYear; avoid unnecessary casts.
3. Venue is dblp:publishedIn (string like short name) and/or dblp:publishedInStream (entity IRI for series/journal/conference). For simple venue text, use dblp:publishedIn.
4. To list an author’s publications: SELECT ?pub WHERE { ?pub dblp:authoredBy <authorIRI> }. Then OPTIONAL get dblp:title, dblp:publishedIn, dblp:yearOfPublication.
5. For yes/no authorship checks, use ASK with dblp:authoredBy, e.g., ASK { <pubIRI> dblp:authoredBy <authorIRI> }.
6. Titles are via dblp:title on publication entities. rdfs:label often exists but is less reliable for titles; prefer dblp:title.
7. If dblp:authoredBy on a pub yields a disambiguation author node (e.g., “… (disambiguation)”), treat it as the author IRI to use in joins; it still identifies the creator.
8. Use dblp:createdBy as an alternative to dblp:authoredBy when authoredBy is missing; both link pubs to creators. Prefer authoredBy for authorship semantics.
9. When filtering by venue names, dblp:publishedIn is a short string (e.g., ‘WSC’, ‘ICALT’, ‘Gov. Inf. Q.’). Avoid FILTER on ?pub IRI strings; filter on dblp:publishedIn value.
10. Avoid rdf:type for pubs; rely on authoredBy/title/publishedIn/yearOfPublication. When counting, use COUNT(DISTINCT ?pub). For average per year, take AVG over yearly counts (subquery GROUP BY year); don’t divide by year-span.
11. Avoid using foaf:name/rdfs:label on creators for joins. Creators expose dblp:creatorName/primaryCreatorName and dblp:primaryAffiliation (string). Prefer joins on IRIs; fetch names/affiliations separately. Use SELECT DISTINCT ?author to dedup.
12. When a SELECT returns no rows unexpectedly, check schema via search_property/search_property_of_entity or list the entity. Many failures stem from using wrong props (dblp:author vs dblp:authoredBy).
13. Negations: avoid tautological NOT EXISTS. Prefer ASK { positive pattern } and invert in prose. For “also published in V?”, test other pubs by same authors and exclude the given pub via FILTER(?other != <pubIRI>) together with dblp:publishedIn 'V'.
14. Avoid text search on titles with CONTAINS/LCASE for exact identification; prefer search_entity to get the record IRI, then query structured triples. After search_entity, verify exact title via dblp:title; don’t pick a “closest match” blindly.
15. Be careful with complex ASK + FILTER combinations; QLever may error (CartesianProductJoin assertion). Simplify logic or split into separate queries to avoid engine bugs.
16. For number of authors, prefer dblp:numberOfCreators when available; otherwise COUNT(DISTINCT ?a) over dblp:authoredBy.

General notes for all knowledge graphs:
1. Normalize NL negations to a clear existential query. Prefer ASK { positive pattern }. For negated questions, evaluate the positive fact and invert only in prose. Avoid tautological or heavy NOT EXISTS patterns that can be slow or misleading.
2. For relative time windows (“last N years”), always use YEAR(NOW()) in SPARQL and align inclusive/exclusive bounds with the question phrasing. Do not hardcode current year in answers; base the conclusion strictly on query results.

You can use the following SPARQL prefixes implicitly in all functions:
bibtex: <http://purl.org/net/nknouf/ns/bibtex#
cito: <http://purl.org/spar/cito/
datacite: <http://purl.org/spar/datacite/
dblp: <https://dblp.org/rdf/schema#
dblps: <https://dblp.org/rdf/schema-2020-07-01#
literal: <http://purl.org/spar/literal/
owl: <http://www.w3.org/2002/07/owl#
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
schema: <http://schema.org/
terms: <http://purl.org/dc/terms/
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Did Leedham, Graham and Wang, Lingyu co-author the paper 'A Thermal Hand Vein Pattern Verification System'?

[Assistant]
To answer this question, I need to find the publication with the exact title "A Thermal Hand Vein Pattern Verification System" in the dblp knowledge graph and then check if both Leedham, Graham and Wang, Lingyu are authors of that publication.

Step 1: Search for the publication entity by its exact title.
Step 2: Check if the publication has both authors Leedham, Graham and Wang, Lingyu.

I will start by searching for the publication entity with the given title.

[Tool]
Top 10 entity alternatives:
1. Lingyu Wang and Graham Leedham: ...tern Verification System. (2005) (<https://dblp.org/rec/conf/icapr/WangL05>)
2. Puneet Gupta et al.: An accurate...ed authentication system. (2016) (<https://dblp.org/rec/journals/kbs/GuptaSG16>)
3. Amioy Kumar et al.: Biometric Au...ermal Hand Vein Patterns. (2009) (<https://dblp.org/rec/conf/dicta/KumarHML09>)
4. Ahmed M. Badawi: Hand Vein Biome... and Patterns Similarity. (2006) (<https://dblp.org/rec/conf/ipcv/Badawi06>)
5. Amit Kumar Singh et al.: Hand ge...ication system: A review. (2009) (<https://dblp.org/rec/conf/icumt/SinghAP09>)
6. Chih-Lung Lin and Kuo-Chin Fan: ...palm-dorsa vein patterns. (2004) (<https://dblp.org/rec/journals/tcsv/LinF04>)
7. Gholamreza Amayeh: A Component-b...nd identification System. (2018) (<https://dblp.org/rec/phd/basesearch/Amayeh18>)
8. Young-Tak Kim et al.: PC-based H...etry Verification System. (2006) (<https://dblp.org/rec/journals/ijflis/KimKLKKLTL06>)
9. Amioy Kumar et al.: Hybrid PSO B...ermal Hand Vein Patterns. (2010) (<https://dblp.org/rec/conf/semcco/KumarHG10>)
10. Dat Tran and Michael Wagner: A P...tern Verification System. (2001) (<https://dblp.org/rec/conf/fuzzIEEE/TranW01>)

[Assistant] I found the publication "A Thermal Hand Vein Pattern Verification System" authored by Lingyu Wang and Graham Leedham in 2005 with the dblp record <https://dblp.org/rec/conf/icapr/WangL05>. Now I will check if both Leedham, Graham and Wang, Lingyu are authors of this publication.

[Tool] True

[Tool]
Got 2 rows and 1 column:
| authorName     |
| -------------- |
| Graham Leedham |
| Lingyu Wang    |

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
ASK WHERE {
  ?pub dblp:title "A Linear Discrete Dynamic System Model for Temporal Gene Interaction and Regulatory Network Influence in Response to Bioethanol Conversion Inhibitor HMF for Ethanologenic Yeast" ; dblp:yearOfPublication 2007 .
}

The publication titled 'A Linear Discrete Dynamic System Model for Temporal Gene Interaction and Regulatory Network Influence in Response to Bioethanol Conversion Inhibitor HMF for Ethanologenic Yeast' was not found to be published in 2007 in the dblp knowledge graph.

Was the publication 'A Linear Discrete Dynamic System Model for Temporal Gene Interaction and Regulatory Network Influence in Response to Bioethanol Conversion Inhibitor HMF for Ethanologenic Yeast' not not published in 2007?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
dblp at https://qlever.cs.uni-freiburg.de/api/dblp with notes:
1. Use dblp:authoredBy to link publications to authors. The inverse (author -> pubs) is not via dblp:author; queries with dblp:author typically return no results.
2. Publication year is dblp:yearOfPublication (xsd:gYear). Avoid dblp:year. For last N years use YEAR(NOW()) in FILTER; use >= for inclusive bounds. Don’t assume current year in prose. MIN/MAX work on gYear; avoid unnecessary casts.
3. Venue is dblp:publishedIn (string like short name) and/or dblp:publishedInStream (entity IRI for series/journal/conference). For simple venue text, use dblp:publishedIn.
4. To list an author’s publications: SELECT ?pub WHERE { ?pub dblp:authoredBy <authorIRI> }. Then OPTIONAL get dblp:title, dblp:publishedIn, dblp:yearOfPublication.
5. For yes/no authorship checks, use ASK with dblp:authoredBy, e.g., ASK { <pubIRI> dblp:authoredBy <authorIRI> }.
6. Titles are via dblp:title on publication entities. rdfs:label often exists but is less reliable for titles; prefer dblp:title.
7. If dblp:authoredBy on a pub yields a disambiguation author node (e.g., “… (disambiguation)”), treat it as the author IRI to use in joins; it still identifies the creator.
8. Use dblp:createdBy as an alternative to dblp:authoredBy when authoredBy is missing; both link pubs to creators. Prefer authoredBy for authorship semantics.
9. When filtering by venue names, dblp:publishedIn is a short string (e.g., ‘WSC’, ‘ICALT’, ‘Gov. Inf. Q.’). Avoid FILTER on ?pub IRI strings; filter on dblp:publishedIn value.
10. Avoid rdf:type for pubs; rely on authoredBy/title/publishedIn/yearOfPublication. When counting, use COUNT(DISTINCT ?pub). For average per year, take AVG over yearly counts (subquery GROUP BY year); don’t divide by year-span.
11. Avoid using foaf:name/rdfs:label on creators for joins. Creators expose dblp:creatorName/primaryCreatorName and dblp:primaryAffiliation (string). Prefer joins on IRIs; fetch names/affiliations separately. Use SELECT DISTINCT ?author to dedup.
12. When a SELECT returns no rows unexpectedly, check schema via search_property/search_property_of_entity or list the entity. Many failures stem from using wrong props (dblp:author vs dblp:authoredBy).
13. Negations: avoid tautological NOT EXISTS. Prefer ASK { positive pattern } and invert in prose. For “also published in V?”, test other pubs by same authors and exclude the given pub via FILTER(?other != <pubIRI>) together with dblp:publishedIn 'V'.
14. Avoid text search on titles with CONTAINS/LCASE for exact identification; prefer search_entity to get the record IRI, then query structured triples. After search_entity, verify exact title via dblp:title; don’t pick a “closest match” blindly.
15. Be careful with complex ASK + FILTER combinations; QLever may error (CartesianProductJoin assertion). Simplify logic or split into separate queries to avoid engine bugs.
16. For number of authors, prefer dblp:numberOfCreators when available; otherwise COUNT(DISTINCT ?a) over dblp:authoredBy.

General notes for all knowledge graphs:
1. Normalize NL negations to a clear existential query. Prefer ASK { positive pattern }. For negated questions, evaluate the positive fact and invert only in prose. Avoid tautological or heavy NOT EXISTS patterns that can be slow or misleading.
2. For relative time windows (“last N years”), always use YEAR(NOW()) in SPARQL and align inclusive/exclusive bounds with the question phrasing. Do not hardcode current year in answers; base the conclusion strictly on query results.

You can use the following SPARQL prefixes implicitly in all functions:
bibtex: <http://purl.org/net/nknouf/ns/bibtex#
cito: <http://purl.org/spar/cito/
datacite: <http://purl.org/spar/datacite/
dblp: <https://dblp.org/rdf/schema#
dblps: <https://dblp.org/rdf/schema-2020-07-01#
literal: <http://purl.org/spar/literal/
owl: <http://www.w3.org/2002/07/owl#
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
schema: <http://schema.org/
terms: <http://purl.org/dc/terms/
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Was the publication 'A Linear Discrete Dynamic System Model for Temporal Gene Interaction and Regulatory Network Influence in Response to Bioethanol Conversion Inhibitor HMF for Ethanologenic Yeast' not not published in 2007?

[Assistant]
The user question is a double negation: "Was the publication ... not not published in 2007?" which simplifies to "Was the publication ... published in 2007?"

Step 1: Identify the publication by its exact title in the dblp knowledge graph.

Step 2: Check if the publication year is 2007.

I will first search for the publication entity by its exact title.

[Tool]
Top 10 entity alternatives:
1. Mingzhou (Joe) Song and Z. Lewis... for Ethanologenic Yeast. (2006) (<https://dblp.org/rec/conf/recomb/SongL06>)
2. Bin Jia and Xiaodong Wang: Regul...latory network inference. (2014) (<https://dblp.org/rec/journals/ejbsb/JiaW14>)
3. Yuexu Jiang et al.: A dynamic pr...pathway model generation. (2020) (<https://dblp.org/rec/journals/bioinformatics/JiangLWXJ20>)
4. Yulan Liang and Arpad Kelemen: B...ene Interaction Networks. (2006) (<https://dblp.org/rec/conf/embc/LiangK06>)
5. Keyi Li et al.: A general model-...onlinear dynamic systems. (2021) (<https://dblp.org/rec/journals/dsp/LiZK21>)
6. Shuqin Zhang et al.: A linear co...netic regulatory network. (2005) (<https://dblp.org/rec/conf/grc/ZhangNCA05>)
7. Thuc Nguyen et al.: A Design Fra...ists' Emotional Response. (2022) (<https://dblp.org/rec/conf/acis/NguyenNVC22>)
8. Ines Hamdi and Mohamed Ben Ahmed...tics Regulatory Networks. (2011) (<https://dblp.org/rec/conf/dexaw/HamdiA11>)
9. Gustavo Arroyo-Figueroa and Raúl...peration Support Systems. (2002) (<https://dblp.org/rec/conf/micai/Arroyo-FigueroaH02>)
10. Xutao Deng et al.: A Dynamic Bay...ng Yeast Genes Functions. (2005) (<https://dblp.org/rec/conf/amcis/DengGA05>)

[Assistant] The exact title of the publication was not found in the top 10 search results. The closest match found is from 2006, but it is not the exact title. I will try a different approach by searching for publications from 2007 with a similar title or keywords to find the exact publication. I will search for publications with the keyword "Bioethanol" in the title from 2007.

[Tool] Got no rows and 3 columns

[Assistant] No publications with the keyword "bioethanol" in the title were found in 2007. I will now try to search for the publication by the author "Mingzhou (Joe) Song" who appears in a similar publication from 2006 to see if the publication is listed under a slightly different year or title.

[Tool]
Top 10 entity alternatives:
1. Mingzhou Song 0001, also known as Mingzhou Song (<https://dblp.org/pid/44/6118>)
2. Songnan Song, also known as Songnan Song (<https://dblp.org/pid/326/8867>)
3. Songtao Song, also known as Songtao Song (<https://dblp.org/pid/314/3752>)
4. Songsong Song, also known as Songsong Song (<https://dblp.org/pid/151/0460>)
5. Songbai Song, also known as Songbai Song (<https://dblp.org/pid/201/8761>)
6. Songbo Song, also known as Songbo Song (<https://dblp.org/pid/40/7457>)
7. Songlin Song, also known as Songlin Song (<https://dblp.org/pid/127/5302>)
8. Songhe Song, also known as Songhe Song (<https://dblp.org/pid/88/8068>)
9. Songzheng Song, also known as Songzheng Song (<https://dblp.org/pid/61/8725>)
10. Song Song, also known as Song Song (<https://dblp.org/pid/88/1952>)

[Assistant] I found an author entity for Mingzhou Song: <https://dblp.org/pid/44/6118>. I will now check the publications authored by this author to find the publication with the given title or a similar one around 2007.

[Tool] Got no rows and 3 columns

[Assistant]
No publications were found authored by Mingzhou Song (https://dblp.org/pid/44/6118) in the years 2006 to 2008. This suggests that the publication with the exact title "A Linear Discrete Dynamic System Model for Temporal Gene Interaction and Regulatory Network Influence in Response to Bioethanol Conversion Inhibitor HMF for Ethanologenic Yeast" might not be present in the dblp knowledge graph or might be under a different author or title.

Given the absence of the exact publication in the dblp data, I cannot confirm if it was published in 2007 or not.

I will now finalize the answer based on this finding.

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT ( COUNT( DISTINCT ?pub ) AS ?count ) WHERE {
  VALUES ?author {
    <https://dblp.org/pid/164/3309> <https://dblp.org/pid/184/6425> <https://dblp.org/pid/q/MeikangQiu>
  }
  ?pub dblp:authoredBy ?author ; dblp:yearOfPublication "2016" ^^ xsd:gYear .
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 43 (xsd:int) |

The authors of 'Cyber Incident Classifications Using Ontology-Based Knowledge Representation for Cybersecurity Insurance in Financial Industry' published 43 papers in the year 2016.

In 2016, how many papers did the authors of 'Cyber Incident Classifications Using Ontology-Based Knowledge Representation for Cybersecurity Insurance in Financial Industry' publish?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
dblp at https://qlever.cs.uni-freiburg.de/api/dblp with notes:
1. Use dblp:authoredBy to link publications to authors. The inverse (author -> pubs) is not via dblp:author; queries with dblp:author typically return no results.
2. Publication year is dblp:yearOfPublication (xsd:gYear). Avoid dblp:year. For last N years use YEAR(NOW()) in FILTER; use >= for inclusive bounds. Don’t assume current year in prose. MIN/MAX work on gYear; avoid unnecessary casts.
3. Venue is dblp:publishedIn (string like short name) and/or dblp:publishedInStream (entity IRI for series/journal/conference). For simple venue text, use dblp:publishedIn.
4. To list an author’s publications: SELECT ?pub WHERE { ?pub dblp:authoredBy <authorIRI> }. Then OPTIONAL get dblp:title, dblp:publishedIn, dblp:yearOfPublication.
5. For yes/no authorship checks, use ASK with dblp:authoredBy, e.g., ASK { <pubIRI> dblp:authoredBy <authorIRI> }.
6. Titles are via dblp:title on publication entities. rdfs:label often exists but is less reliable for titles; prefer dblp:title.
7. If dblp:authoredBy on a pub yields a disambiguation author node (e.g., “… (disambiguation)”), treat it as the author IRI to use in joins; it still identifies the creator.
8. Use dblp:createdBy as an alternative to dblp:authoredBy when authoredBy is missing; both link pubs to creators. Prefer authoredBy for authorship semantics.
9. When filtering by venue names, dblp:publishedIn is a short string (e.g., ‘WSC’, ‘ICALT’, ‘Gov. Inf. Q.’). Avoid FILTER on ?pub IRI strings; filter on dblp:publishedIn value.
10. Avoid rdf:type for pubs; rely on authoredBy/title/publishedIn/yearOfPublication. When counting, use COUNT(DISTINCT ?pub). For average per year, take AVG over yearly counts (subquery GROUP BY year); don’t divide by year-span.
11. Avoid using foaf:name/rdfs:label on creators for joins. Creators expose dblp:creatorName/primaryCreatorName and dblp:primaryAffiliation (string). Prefer joins on IRIs; fetch names/affiliations separately. Use SELECT DISTINCT ?author to dedup.
12. When a SELECT returns no rows unexpectedly, check schema via search_property/search_property_of_entity or list the entity. Many failures stem from using wrong props (dblp:author vs dblp:authoredBy).
13. Negations: avoid tautological NOT EXISTS. Prefer ASK { positive pattern } and invert in prose. For “also published in V?”, test other pubs by same authors and exclude the given pub via FILTER(?other != <pubIRI>) together with dblp:publishedIn 'V'.
14. Avoid text search on titles with CONTAINS/LCASE for exact identification; prefer search_entity to get the record IRI, then query structured triples. After search_entity, verify exact title via dblp:title; don’t pick a “closest match” blindly.
15. Be careful with complex ASK + FILTER combinations; QLever may error (CartesianProductJoin assertion). Simplify logic or split into separate queries to avoid engine bugs.
16. For number of authors, prefer dblp:numberOfCreators when available; otherwise COUNT(DISTINCT ?a) over dblp:authoredBy.

General notes for all knowledge graphs:
1. Normalize NL negations to a clear existential query. Prefer ASK { positive pattern }. For negated questions, evaluate the positive fact and invert only in prose. Avoid tautological or heavy NOT EXISTS patterns that can be slow or misleading.
2. For relative time windows (“last N years”), always use YEAR(NOW()) in SPARQL and align inclusive/exclusive bounds with the question phrasing. Do not hardcode current year in answers; base the conclusion strictly on query results.

You can use the following SPARQL prefixes implicitly in all functions:
bibtex: <http://purl.org/net/nknouf/ns/bibtex#
cito: <http://purl.org/spar/cito/
datacite: <http://purl.org/spar/datacite/
dblp: <https://dblp.org/rdf/schema#
dblps: <https://dblp.org/rdf/schema-2020-07-01#
literal: <http://purl.org/spar/literal/
owl: <http://www.w3.org/2002/07/owl#
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
schema: <http://schema.org/
terms: <http://purl.org/dc/terms/
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] In 2016, how many papers did the authors of 'Cyber Incident Classifications Using Ontology-Based Knowledge Representation for Cybersecurity Insurance in Financial Industry' publish?

[Assistant]
To answer this question, I need to follow these steps:
1. Find the publication with the title "Cyber Incident Classifications Using Ontology-Based Knowledge Representation for Cybersecurity Insurance in Financial Industry" to get its authors.
2. Retrieve the authors of this publication.
3. Count how many papers these authors published in the year 2016.

I will start by searching for the publication entity by its exact title.

[Tool]
Top 10 entity alternatives:
1. Sam Adam Elnagdy et al.: Cyber I...ce in Financial Industry. (2016) (<https://dblp.org/rec/conf/cscloud/ElnagdyQG16a>)
2. Keke Gai et al.: Secure cyber in...rance in cloud computing. (2017) (<https://dblp.org/rec/journals/concurrency/GaiQH17>)
3. Sam Adam Elnagdy et al.: Underst...ustry in Cloud Computing. (2016) (<https://dblp.org/rec/conf/cscloud/ElnagdyQG16>)
4. Patrick Andrei Caron Guerra et a...ent Resolution Knowledge. (2023) (<https://dblp.org/rec/conf/ladc/GuerraBNFS23>)
5. Keke Gai et al.: Security-Aware ...nt in Financial Big Data. (2016) (<https://dblp.org/rec/conf/bigdatasec/GaiQE16a>)
6. Kao-Yi Shen et al.: Financial mo... based hybrid MCDM model. (2017) (<https://dblp.org/rec/journals/isci/ShenHT17>)
7. Maja Videnovik et al.: Using Pee...urity in Primary Schools. (2025) (<https://dblp.org/rec/journals/access/VidenovikTVKBF25>)
8. Keke Gai et al.: A Novel Secure ... Cybersecurity Insurance. (2016) (<https://dblp.org/rec/conf/bigdatasec/GaiQE16>)
9. Miroslav Kis and Bobby Singh: A ...n the Financial Industry. (2018) (<https://dblp.org/rec/conf/ithings/KisS18>)
10. International Workshop on CyberS...r Industry and Academia (CSE4IA) (<https://dblp.org/streams/conf/cse4ia>)

[Assistant] I found the publication "Cyber Incident Classifications Using Ontology-Based Knowledge Representation for Cybersecurity Insurance in Financial Industry" with the IRI <https://dblp.org/rec/conf/cscloud/ElnagdyQG16a>. Next, I will retrieve the authors of this publication.

[Tool]
Got 3 rows and 1 column:
| author                                             |
| -------------------------------------------------- |
| Keke Gai (<https://dblp.org/pid/164/3309>)         |
| Sam Adam Elnagdy (<https://dblp.org/pid/184/6425>) |
| Meikang Qiu (<https://dblp.org/pid/q/MeikangQiu>)  |

[Assistant] The authors of the publication are Keke Gai, Sam Adam Elnagdy, and Meikang Qiu. Now, I will count how many papers these authors published in the year 2016.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 43 (xsd:int) |

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
SELECT ?wikidataID WHERE {
  <https://dblp.org/pid/o/AJeffersonOffutt> dblp:wikidata ?wikidataID .
}

Got 1 row and 1 column:
| wikidataID  |
| ----------- |
| wd:Q6174621 |

The Wikidata ID of Offutt, A. Jefferson is wd:Q6174621.

What is the Wikidata ID of Offutt, A. Jefferson?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
dblp at https://qlever.cs.uni-freiburg.de/api/dblp with notes:
1. Use dblp:authoredBy to link publications to authors. The inverse (author -> pubs) is not via dblp:author; queries with dblp:author typically return no results.
2. Publication year is dblp:yearOfPublication (xsd:gYear). Avoid dblp:year. For last N years use YEAR(NOW()) in FILTER; use >= for inclusive bounds. Don’t assume current year in prose. MIN/MAX work on gYear; avoid unnecessary casts.
3. Venue is dblp:publishedIn (string like short name) and/or dblp:publishedInStream (entity IRI for series/journal/conference). For simple venue text, use dblp:publishedIn.
4. To list an author’s publications: SELECT ?pub WHERE { ?pub dblp:authoredBy <authorIRI> }. Then OPTIONAL get dblp:title, dblp:publishedIn, dblp:yearOfPublication.
5. For yes/no authorship checks, use ASK with dblp:authoredBy, e.g., ASK { <pubIRI> dblp:authoredBy <authorIRI> }.
6. Titles are via dblp:title on publication entities. rdfs:label often exists but is less reliable for titles; prefer dblp:title.
7. If dblp:authoredBy on a pub yields a disambiguation author node (e.g., “… (disambiguation)”), treat it as the author IRI to use in joins; it still identifies the creator.
8. Use dblp:createdBy as an alternative to dblp:authoredBy when authoredBy is missing; both link pubs to creators. Prefer authoredBy for authorship semantics.
9. When filtering by venue names, dblp:publishedIn is a short string (e.g., ‘WSC’, ‘ICALT’, ‘Gov. Inf. Q.’). Avoid FILTER on ?pub IRI strings; filter on dblp:publishedIn value.
10. Avoid rdf:type for pubs; rely on authoredBy/title/publishedIn/yearOfPublication. When counting, use COUNT(DISTINCT ?pub). For average per year, take AVG over yearly counts (subquery GROUP BY year); don’t divide by year-span.
11. Avoid using foaf:name/rdfs:label on creators for joins. Creators expose dblp:creatorName/primaryCreatorName and dblp:primaryAffiliation (string). Prefer joins on IRIs; fetch names/affiliations separately. Use SELECT DISTINCT ?author to dedup.
12. When a SELECT returns no rows unexpectedly, check schema via search_property/search_property_of_entity or list the entity. Many failures stem from using wrong props (dblp:author vs dblp:authoredBy).
13. Negations: avoid tautological NOT EXISTS. Prefer ASK { positive pattern } and invert in prose. For “also published in V?”, test other pubs by same authors and exclude the given pub via FILTER(?other != <pubIRI>) together with dblp:publishedIn 'V'.
14. Avoid text search on titles with CONTAINS/LCASE for exact identification; prefer search_entity to get the record IRI, then query structured triples. After search_entity, verify exact title via dblp:title; don’t pick a “closest match” blindly.
15. Be careful with complex ASK + FILTER combinations; QLever may error (CartesianProductJoin assertion). Simplify logic or split into separate queries to avoid engine bugs.
16. For number of authors, prefer dblp:numberOfCreators when available; otherwise COUNT(DISTINCT ?a) over dblp:authoredBy.

General notes for all knowledge graphs:
1. Normalize NL negations to a clear existential query. Prefer ASK { positive pattern }. For negated questions, evaluate the positive fact and invert only in prose. Avoid tautological or heavy NOT EXISTS patterns that can be slow or misleading.
2. For relative time windows (“last N years”), always use YEAR(NOW()) in SPARQL and align inclusive/exclusive bounds with the question phrasing. Do not hardcode current year in answers; base the conclusion strictly on query results.

You can use the following SPARQL prefixes implicitly in all functions:
bibtex: <http://purl.org/net/nknouf/ns/bibtex#
cito: <http://purl.org/spar/cito/
datacite: <http://purl.org/spar/datacite/
dblp: <https://dblp.org/rdf/schema#
dblps: <https://dblp.org/rdf/schema-2020-07-01#
literal: <http://purl.org/spar/literal/
owl: <http://www.w3.org/2002/07/owl#
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
schema: <http://schema.org/
terms: <http://purl.org/dc/terms/
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What is the Wikidata ID of Offutt, A. Jefferson?

[Assistant] I will start by searching for the entity "Offutt, A. Jefferson" in the dblp knowledge graph to see if there is an author entity for this person. Then I will check if there is a corresponding Wikidata ID linked to that author entity.

[Tool]
Top 10 entity alternatives:
1. A. Jefferson Offutt, also known as A. Jefferson Offutt (<https://dblp.org/pid/o/AJeffersonOffutt>)
2. A. Jefferson Offutt: Comments on Tai. (1990) (<https://dblp.org/rec/journals/sigsoft/Offutt90>)
3. A. Jefferson Offutt: Quality Att...eb Software Applications. (2002) (<https://dblp.org/rec/journals/software/Offutt02>)
4. Zhenyi Jin and A. Jefferson Offu...ased Integration Testing. (1996) (<https://dblp.org/rec/conf/iceccs/JinO96>)
5. A. Jefferson Offutt and Aynur Ab... from UML Specifications. (1999) (<https://dblp.org/rec/conf/uml/OffuttA99>)
6. A. Jefferson Offutt: Unit Testin...rsus Integration Testing. (1991) (<https://dblp.org/rec/conf/itc/Offutt91>)
7. A. Jefferson Offutt: An integrat...t data generation system. (1991) (<https://dblp.org/rec/journals/jsi/Offutt91>)
8. Mohammad Abu-Matar and A. Jeffer...itecture Empirical Study. (2007) (<https://dblp.org/rec/conf/seke/Abu-MatarO07>)
9. Richard A. DeMillo and A. Jeffer...tic Test Data Generation. (1991) (<https://dblp.org/rec/journals/tse/DeMilloO91>)
10. A. Jefferson Offutt et al.: An A...ased Integration Testing. (2000) (<https://dblp.org/rec/conf/iceccs/OffuttAA00>)

[Assistant] I found an author entity for "A. Jefferson Offutt" in the dblp knowledge graph with the IRI: <https://dblp.org/pid/o/AJeffersonOffutt>. Next, I will check if there is a Wikidata ID associated with this author entity.

[Tool]
Got 30 rows and 3 columns, showing the first 10 rows below:
| subject                                                         | property                                     | object                                          |
| --------------------------------------------------------------- | -------------------------------------------- | ----------------------------------------------- |
| A. Jefferson Offutt (<https://dblp.org/pid/o/AJeffersonOffutt>) | creatorname (dblp:creatorName)               | A. Jefferson Offutt                             |
| A. Jefferson Offutt (<https://dblp.org/pid/o/AJeffersonOffutt>) | primaryCreatorName (dblp:primaryCreatorName) | A. Jefferson Offutt                             |
| A. Jefferson Offutt (<https://dblp.org/pid/o/AJeffersonOffutt>) | wikidata (dblp:wikidata)                     | wd:Q6174621                                     |
| A. Jefferson Offutt (<https://dblp.org/pid/o/AJeffersonOffutt>) | affiliation (dblp:affiliation)               | George Mason University, Fairfax, Virginia, USA |
| A. Jefferson Offutt (<https://dblp.org/pid/o/AJeffersonOffutt>) | orcid (dblp:orcid)                           | <https://orcid.org/0000-0002-8657-2557>         |
| A. Jefferson Offutt (<https://dblp.org/pid/o/AJeffersonOffutt>) | primaryAffiliation (dblp:primaryAffiliation) | George Mason University, Fairfax, Virginia, USA |
| A. Jefferson Offutt (<https://dblp.org/pid/o/AJeffersonOffutt>) | webpage (dblp:webpage)                       | <https://dl.acm.org/profile/81100103291>        |
| A. Jefferson Offutt (<https://dblp.org/pid/o/AJeffersonOffutt>) | homepage (dblp:homepage)                     | <http://www.cs.gmu.edu/~offutt/>                |
| A. Jefferson Offutt (<https://dblp.org/pid/o/AJeffersonOffutt>) | primaryHomepage (dblp:primaryHomepage)       | <http://www.cs.gmu.edu/~offutt/>                |
| A. Jefferson Offutt (<https://dblp.org/pid/o/AJeffersonOffutt>) | wikipedia (dblp:wikipedia)                   | <https://en.wikipedia.org/wiki/Jeff_Offutt>     |
| ...                                                             | ...                                          | ...                                             |

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
SELECT ?venue WHERE {
  <https://dblp.org/rec/journals/jlp/ShieberSP95> dblp:publishedIn ?venue
}

Got 1 row and 1 column:
| venue            |
| ---------------- |
| J. Log. Program. |

The paper 'Principles and Implementation of Deductive Parsing' was published in the venue 'J. Log. Program.'.

Find the venue in which the paper 'Principles and Implementation of Deductive Parsing' was published.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
dblp at https://qlever.cs.uni-freiburg.de/api/dblp with notes:
1. Use dblp:authoredBy to link publications to authors. The inverse (author -> pubs) is not via dblp:author; queries with dblp:author typically return no results.
2. Publication year is dblp:yearOfPublication (xsd:gYear). Avoid dblp:year. For last N years use YEAR(NOW()) in FILTER; use >= for inclusive bounds. Don’t assume current year in prose. MIN/MAX work on gYear; avoid unnecessary casts.
3. Venue is dblp:publishedIn (string like short name) and/or dblp:publishedInStream (entity IRI for series/journal/conference). For simple venue text, use dblp:publishedIn.
4. To list an author’s publications: SELECT ?pub WHERE { ?pub dblp:authoredBy <authorIRI> }. Then OPTIONAL get dblp:title, dblp:publishedIn, dblp:yearOfPublication.
5. For yes/no authorship checks, use ASK with dblp:authoredBy, e.g., ASK { <pubIRI> dblp:authoredBy <authorIRI> }.
6. Titles are via dblp:title on publication entities. rdfs:label often exists but is less reliable for titles; prefer dblp:title.
7. If dblp:authoredBy on a pub yields a disambiguation author node (e.g., “… (disambiguation)”), treat it as the author IRI to use in joins; it still identifies the creator.
8. Use dblp:createdBy as an alternative to dblp:authoredBy when authoredBy is missing; both link pubs to creators. Prefer authoredBy for authorship semantics.
9. When filtering by venue names, dblp:publishedIn is a short string (e.g., ‘WSC’, ‘ICALT’, ‘Gov. Inf. Q.’). Avoid FILTER on ?pub IRI strings; filter on dblp:publishedIn value.
10. Avoid rdf:type for pubs; rely on authoredBy/title/publishedIn/yearOfPublication. When counting, use COUNT(DISTINCT ?pub). For average per year, take AVG over yearly counts (subquery GROUP BY year); don’t divide by year-span.
11. Avoid using foaf:name/rdfs:label on creators for joins. Creators expose dblp:creatorName/primaryCreatorName and dblp:primaryAffiliation (string). Prefer joins on IRIs; fetch names/affiliations separately. Use SELECT DISTINCT ?author to dedup.
12. When a SELECT returns no rows unexpectedly, check schema via search_property/search_property_of_entity or list the entity. Many failures stem from using wrong props (dblp:author vs dblp:authoredBy).
13. Negations: avoid tautological NOT EXISTS. Prefer ASK { positive pattern } and invert in prose. For “also published in V?”, test other pubs by same authors and exclude the given pub via FILTER(?other != <pubIRI>) together with dblp:publishedIn 'V'.
14. Avoid text search on titles with CONTAINS/LCASE for exact identification; prefer search_entity to get the record IRI, then query structured triples. After search_entity, verify exact title via dblp:title; don’t pick a “closest match” blindly.
15. Be careful with complex ASK + FILTER combinations; QLever may error (CartesianProductJoin assertion). Simplify logic or split into separate queries to avoid engine bugs.
16. For number of authors, prefer dblp:numberOfCreators when available; otherwise COUNT(DISTINCT ?a) over dblp:authoredBy.

General notes for all knowledge graphs:
1. Normalize NL negations to a clear existential query. Prefer ASK { positive pattern }. For negated questions, evaluate the positive fact and invert only in prose. Avoid tautological or heavy NOT EXISTS patterns that can be slow or misleading.
2. For relative time windows (“last N years”), always use YEAR(NOW()) in SPARQL and align inclusive/exclusive bounds with the question phrasing. Do not hardcode current year in answers; base the conclusion strictly on query results.

You can use the following SPARQL prefixes implicitly in all functions:
bibtex: <http://purl.org/net/nknouf/ns/bibtex#
cito: <http://purl.org/spar/cito/
datacite: <http://purl.org/spar/datacite/
dblp: <https://dblp.org/rdf/schema#
dblps: <https://dblp.org/rdf/schema-2020-07-01#
literal: <http://purl.org/spar/literal/
owl: <http://www.w3.org/2002/07/owl#
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
schema: <http://schema.org/
terms: <http://purl.org/dc/terms/
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Find the venue in which the paper 'Principles and Implementation of Deductive Parsing' was published.

[Assistant] To find the venue in which the paper titled "Principles and Implementation of Deductive Parsing" was published, I will first search for the entity corresponding to this paper in the dblp knowledge graph. Then, I will query the publication venue for this paper using the appropriate property.

[Tool]
Top 10 entity alternatives:
1. Stuart M. Shieber et al.: Princi...ion of Deductive Parsing. (1995) (<https://dblp.org/rec/journals/jlp/ShieberSP95>)
2. Stuart M. Shieber et al.: Princi...ion of Deductive Parsing. (1994) (<https://dblp.org/rec/journals/corr/ShieberSP94>)
3. Gang Tan: Principles and Impleme...re-Based Fault Isolation. (2017) (<https://dblp.org/rec/journals/ftsec/Tan17>)
4. Gregers Koch: About Application ...of Semantic Meta Parsing. (2005) (<https://dblp.org/rec/conf/somet/Koch05>)
5. Chenming Zhang: Interpretation o...of FreeRider: A tutorial. (2023) (<https://dblp.org/rec/journals/corr/abs-2305-10316>)
6. Andreas Richtsfeld et al.: Imple... for object segmentation. (2012) (<https://dblp.org/rec/conf/icpr/RichtsfeldZV12>)
7. Ulrik Petersen: Principles, Impl...of a Corpus Query System. (2005) (<https://dblp.org/rec/conf/fsmnlp/Petersen05>)
8. Andrzej Ziabicki: The theory of ... computer implementation. (1992) (<https://dblp.org/rec/journals/lre/Ziabicki92>)
9. Mengchi Liu: Design and Implemen...Oriented Database System. (2000) (<https://dblp.org/rec/journals/jiis/Liu00>)
10. Kushal Ajaybhai Anjaria: Computa...a stewardship principles. (2020) (<https://dblp.org/rec/journals/program/Anjaria20>)

[Assistant]
I found two papers with titles matching "Principles and Implementation of Deductive Parsing":
1. https://dblp.org/rec/journals/jlp/ShieberSP95 (published in 1995)
2. https://dblp.org/rec/journals/corr/ShieberSP94 (published in 1994)

I will now query the venue where the first paper (https://dblp.org/rec/journals/jlp/ShieberSP95) was published.

[Tool]
Got 1 row and 1 column:
| venue            |
| ---------------- |
| J. Log. Program. |

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
SELECT DISTINCT ?venue WHERE {
  VALUES ?author {
    <https://dblp.org/pid/19/2932-1> <https://dblp.org/pid/236/3060> <https://dblp.org/pid/40/4160> <https://dblp.org/pid/40/4731> <https://dblp.org/pid/55/2484-1>
  }
  ?pub dblp:authoredBy ?author ; dblp:publishedIn ?venue .
  FILTER ( ?pub != <https://dblp.org/rec/conf/fgcn/ChenZXSS08> )
}

Got 397 rows and 1 column, showing the first 5 and last 5 rows below:
| venue                |
| -------------------- |
| 6GN                  |
| AAAI                 |
| AAMAS                |
| ACC                  |
| ACM Comput. Surv.    |
| ...                  |
| Wirel. Networks      |
| Wirel. Pers. Commun. |
| WOWMOM               |
| WWW                  |
| 计算机科学                |

The other publications by the authors of 'The Development of a Realistic Simulation Framework with OMNeT++' were published in various venues including 6GN, AAAI, AAMAS, ACC, ACM Comput. Surv., Wirel. Networks, Wirel. Pers. Commun., WOWMOM, WWW, and 计算机科学 among others.

In which venues were the other publications published by the authors of 'The Development of a Realistic Simulation Framework with OMNeT++'?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
dblp at https://qlever.cs.uni-freiburg.de/api/dblp with notes:
1. Use dblp:authoredBy to link publications to authors. The inverse (author -> pubs) is not via dblp:author; queries with dblp:author typically return no results.
2. Publication year is dblp:yearOfPublication (xsd:gYear). Avoid dblp:year. For last N years use YEAR(NOW()) in FILTER; use >= for inclusive bounds. Don’t assume current year in prose. MIN/MAX work on gYear; avoid unnecessary casts.
3. Venue is dblp:publishedIn (string like short name) and/or dblp:publishedInStream (entity IRI for series/journal/conference). For simple venue text, use dblp:publishedIn.
4. To list an author’s publications: SELECT ?pub WHERE { ?pub dblp:authoredBy <authorIRI> }. Then OPTIONAL get dblp:title, dblp:publishedIn, dblp:yearOfPublication.
5. For yes/no authorship checks, use ASK with dblp:authoredBy, e.g., ASK { <pubIRI> dblp:authoredBy <authorIRI> }.
6. Titles are via dblp:title on publication entities. rdfs:label often exists but is less reliable for titles; prefer dblp:title.
7. If dblp:authoredBy on a pub yields a disambiguation author node (e.g., “… (disambiguation)”), treat it as the author IRI to use in joins; it still identifies the creator.
8. Use dblp:createdBy as an alternative to dblp:authoredBy when authoredBy is missing; both link pubs to creators. Prefer authoredBy for authorship semantics.
9. When filtering by venue names, dblp:publishedIn is a short string (e.g., ‘WSC’, ‘ICALT’, ‘Gov. Inf. Q.’). Avoid FILTER on ?pub IRI strings; filter on dblp:publishedIn value.
10. Avoid rdf:type for pubs; rely on authoredBy/title/publishedIn/yearOfPublication. When counting, use COUNT(DISTINCT ?pub). For average per year, take AVG over yearly counts (subquery GROUP BY year); don’t divide by year-span.
11. Avoid using foaf:name/rdfs:label on creators for joins. Creators expose dblp:creatorName/primaryCreatorName and dblp:primaryAffiliation (string). Prefer joins on IRIs; fetch names/affiliations separately. Use SELECT DISTINCT ?author to dedup.
12. When a SELECT returns no rows unexpectedly, check schema via search_property/search_property_of_entity or list the entity. Many failures stem from using wrong props (dblp:author vs dblp:authoredBy).
13. Negations: avoid tautological NOT EXISTS. Prefer ASK { positive pattern } and invert in prose. For “also published in V?”, test other pubs by same authors and exclude the given pub via FILTER(?other != <pubIRI>) together with dblp:publishedIn 'V'.
14. Avoid text search on titles with CONTAINS/LCASE for exact identification; prefer search_entity to get the record IRI, then query structured triples. After search_entity, verify exact title via dblp:title; don’t pick a “closest match” blindly.
15. Be careful with complex ASK + FILTER combinations; QLever may error (CartesianProductJoin assertion). Simplify logic or split into separate queries to avoid engine bugs.
16. For number of authors, prefer dblp:numberOfCreators when available; otherwise COUNT(DISTINCT ?a) over dblp:authoredBy.

General notes for all knowledge graphs:
1. Normalize NL negations to a clear existential query. Prefer ASK { positive pattern }. For negated questions, evaluate the positive fact and invert only in prose. Avoid tautological or heavy NOT EXISTS patterns that can be slow or misleading.
2. For relative time windows (“last N years”), always use YEAR(NOW()) in SPARQL and align inclusive/exclusive bounds with the question phrasing. Do not hardcode current year in answers; base the conclusion strictly on query results.

You can use the following SPARQL prefixes implicitly in all functions:
bibtex: <http://purl.org/net/nknouf/ns/bibtex#
cito: <http://purl.org/spar/cito/
datacite: <http://purl.org/spar/datacite/
dblp: <https://dblp.org/rdf/schema#
dblps: <https://dblp.org/rdf/schema-2020-07-01#
literal: <http://purl.org/spar/literal/
owl: <http://www.w3.org/2002/07/owl#
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
schema: <http://schema.org/
terms: <http://purl.org/dc/terms/
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] In which venues were the other publications published by the authors of 'The Development of a Realistic Simulation Framework with OMNeT++'?

[Assistant]
To answer the question "In which venues were the other publications published by the authors of 'The Development of a Realistic Simulation Framework with OMNeT++'?", I will follow these steps:

1. Identify the publication entity for the paper titled "The Development of a Realistic Simulation Framework with OMNeT++".
2. Retrieve the authors of this publication.
3. Retrieve other publications by these authors, excluding the original publication.
4. Retrieve the venues where these other publications were published.

I will start by searching for the publication entity with the exact title "The Development of a Realistic Simulation Framework with OMNeT++".

[Tool]
Top 10 entity alternatives:
1. Jiming Chen et al.: The Developm...n Framework with OMNeT++. (2008) (<https://dblp.org/rec/conf/fgcn/ChenZXSS08>)
2. Anthony Bilodeau et al.: Develop...c simulation with pySTED. (2024) (<https://dblp.org/rec/journals/natmi/BilodeauMCTHDL24>)
3. Wenjie Zeng et al.: Development ...FETR with BMUS framework. (2025) (<https://dblp.org/rec/journals/ress/ZengLGL25>)
4. Dieter Hildebrandt and Wilhelm H...ethodology and framework. (2008) (<https://dblp.org/rec/journals/jsa/HildebrandtH08>)
5. Alberto Falcone et al.: Simplify...software framework (DKF). (2017) (<https://dblp.org/rec/conf/dsrt/FalconeGTA17>)
6. Hugo López-Fernández et al.: Rap...th the AIBench framework. (2011) (<https://dblp.org/rec/journals/jib/Lopez-FernandezRGRSCCF11>)
7. Daniele Gianni et al.: DisSimJAD...buted simulation systems. (2009) (<https://dblp.org/rec/conf/simutools/GianniDI09>)
8. Anastasia Angelopoulou et al.: A...nalysis simulation model. (2015) (<https://dblp.org/rec/conf/cogsima/AngelopoulouMK15>)
9. David Tai et al.: Development of...rd Architectural Pattern. (2018) (<https://dblp.org/rec/conf/apsec/TaiWL18>)
10. Arnaud Degroote et al.: Integrat...thin the MORSE framework. (2016) (<https://dblp.org/rec/conf/iros/DegrooteKL16>)

[Assistant]
I found the publication "The Development of a Realistic Simulation Framework with OMNeT++" with the entity IRI <https://dblp.org/rec/conf/fgcn/ChenZXSS08>.

Next, I will retrieve the authors of this publication.

[Tool]
Got 5 rows and 1 column:
| author                                                          |
| --------------------------------------------------------------- |
| Lei Shu 0001 (<https://dblp.org/pid/19/2932-1>)                 |
| Weiqiang Xu (disambiguation) (<https://dblp.org/pid/236/3060>)  |
| Youxian Sun (<https://dblp.org/pid/40/4160>)                    |
| Jianhui Zhang (disambiguation) (<https://dblp.org/pid/40/4731>) |
| Jiming Chen 0001 (<https://dblp.org/pid/55/2484-1>)             |

[Assistant]
The authors of the publication "The Development of a Realistic Simulation Framework with OMNeT++" are:
- Lei Shu 0001 (https://dblp.org/pid/19/2932-1)
- Weiqiang Xu (disambiguation) (https://dblp.org/pid/236/3060)
- Youxian Sun (https://dblp.org/pid/40/4160)
- Jianhui Zhang (disambiguation) (https://dblp.org/pid/40/4731)
- Jiming Chen 0001 (https://dblp.org/pid/55/2484-1)

Now I will retrieve the other publications by these authors, excluding the original publication, and get the venues where these other publications were published.

[Tool]
Got 397 rows and 1 column, showing the first 5 and last 5 rows below:
| venue                |
| -------------------- |
| 6GN                  |
| AAAI                 |
| AAMAS                |
| ACC                  |
| ACM Comput. Surv.    |
| ...                  |
| Wirel. Networks      |
| Wirel. Pers. Commun. |
| WOWMOM               |
| WWW                  |
| 计算机科学                |

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
SELECT ?pub ?title WHERE {
  ?pub dblp:authoredBy <https://dblp.org/pid/63/10539> .
  OPTIONAL {
    ?pub dblp:title ?title
  }
}

Got 2 rows and 2 columns:
| pub                                                                                | title                                                               |
| ----------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------- |
| Joaquin Alder Silva-Faundez et a...development and research. (2011) (<https://dblp.org/rec/conf/larc/Silva-FaundezFD11>)      | Senor Maderita: A semi-omnidirec...ining, development and research. |
| Joaquin Alder Silva-Faundez et a... Mobile Units Using WSNs. (2015) (<https://dblp.org/rec/journals/ijccc/Silva-FaundezDM15>) | An Anticipatory Control for a Fl...tion of Mobile Units Using WSNs. |

The author Silva-Faundez, Joaquin Alder wrote the following papers:
1. Senor Maderita: A semi-omnidirectional wireless sensor network for mining, development and research. (2011) - https://dblp.org/rec/conf/larc/Silva-FaundezFD11
2. An Anticipatory Control for a Fleet Formation of Mobile Units Using WSNs. (2015) - https://dblp.org/rec/journals/ijccc/Silva-FaundezDM15

Which papers did the author Silva-Faundez, Joaquin Alder write?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
dblp at https://qlever.cs.uni-freiburg.de/api/dblp with notes:
1. Use dblp:authoredBy to link publications to authors. The inverse (author -> pubs) is not via dblp:author; queries with dblp:author typically return no results.
2. Publication year is dblp:yearOfPublication (xsd:gYear). Avoid dblp:year. For last N years use YEAR(NOW()) in FILTER; use >= for inclusive bounds. Don’t assume current year in prose. MIN/MAX work on gYear; avoid unnecessary casts.
3. Venue is dblp:publishedIn (string like short name) and/or dblp:publishedInStream (entity IRI for series/journal/conference). For simple venue text, use dblp:publishedIn.
4. To list an author’s publications: SELECT ?pub WHERE { ?pub dblp:authoredBy <authorIRI> }. Then OPTIONAL get dblp:title, dblp:publishedIn, dblp:yearOfPublication.
5. For yes/no authorship checks, use ASK with dblp:authoredBy, e.g., ASK { <pubIRI> dblp:authoredBy <authorIRI> }.
6. Titles are via dblp:title on publication entities. rdfs:label often exists but is less reliable for titles; prefer dblp:title.
7. If dblp:authoredBy on a pub yields a disambiguation author node (e.g., “… (disambiguation)”), treat it as the author IRI to use in joins; it still identifies the creator.
8. Use dblp:createdBy as an alternative to dblp:authoredBy when authoredBy is missing; both link pubs to creators. Prefer authoredBy for authorship semantics.
9. When filtering by venue names, dblp:publishedIn is a short string (e.g., ‘WSC’, ‘ICALT’, ‘Gov. Inf. Q.’). Avoid FILTER on ?pub IRI strings; filter on dblp:publishedIn value.
10. Avoid rdf:type for pubs; rely on authoredBy/title/publishedIn/yearOfPublication. When counting, use COUNT(DISTINCT ?pub). For average per year, take AVG over yearly counts (subquery GROUP BY year); don’t divide by year-span.
11. Avoid using foaf:name/rdfs:label on creators for joins. Creators expose dblp:creatorName/primaryCreatorName and dblp:primaryAffiliation (string). Prefer joins on IRIs; fetch names/affiliations separately. Use SELECT DISTINCT ?author to dedup.
12. When a SELECT returns no rows unexpectedly, check schema via search_property/search_property_of_entity or list the entity. Many failures stem from using wrong props (dblp:author vs dblp:authoredBy).
13. Negations: avoid tautological NOT EXISTS. Prefer ASK { positive pattern } and invert in prose. For “also published in V?”, test other pubs by same authors and exclude the given pub via FILTER(?other != <pubIRI>) together with dblp:publishedIn 'V'.
14. Avoid text search on titles with CONTAINS/LCASE for exact identification; prefer search_entity to get the record IRI, then query structured triples. After search_entity, verify exact title via dblp:title; don’t pick a “closest match” blindly.
15. Be careful with complex ASK + FILTER combinations; QLever may error (CartesianProductJoin assertion). Simplify logic or split into separate queries to avoid engine bugs.
16. For number of authors, prefer dblp:numberOfCreators when available; otherwise COUNT(DISTINCT ?a) over dblp:authoredBy.

General notes for all knowledge graphs:
1. Normalize NL negations to a clear existential query. Prefer ASK { positive pattern }. For negated questions, evaluate the positive fact and invert only in prose. Avoid tautological or heavy NOT EXISTS patterns that can be slow or misleading.
2. For relative time windows (“last N years”), always use YEAR(NOW()) in SPARQL and align inclusive/exclusive bounds with the question phrasing. Do not hardcode current year in answers; base the conclusion strictly on query results.

You can use the following SPARQL prefixes implicitly in all functions:
bibtex: <http://purl.org/net/nknouf/ns/bibtex#
cito: <http://purl.org/spar/cito/
datacite: <http://purl.org/spar/datacite/
dblp: <https://dblp.org/rdf/schema#
dblps: <https://dblp.org/rdf/schema-2020-07-01#
literal: <http://purl.org/spar/literal/
owl: <http://www.w3.org/2002/07/owl#
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
schema: <http://schema.org/
terms: <http://purl.org/dc/terms/
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Which papers did the author Silva-Faundez, Joaquin Alder write?

[Assistant] To answer the question about which papers the author Silva-Faundez, Joaquin Alder wrote, I need to find the author entity for "Silva-Faundez, Joaquin Alder" in the dblp knowledge graph and then retrieve the publications authored by this entity. I will start by searching for the author entity using the name.

[Tool]
Top 10 entity alternatives:
1. Joaquin Alder Silva-Faundez, also known as Joaquin Alder Silva-Faundez (<https://dblp.org/pid/63/10539>)
2. Joaquín García 0001, also known as Joaquín García (<https://dblp.org/pid/g/JoaquinGarcia>)
3. Joaquin Vanschoren, also known as Joaquin Vanschoren (<https://dblp.org/pid/85/5045>)
4. Joaquín Izquierdo 0001, also known as Joaquín Izquierdo (<https://dblp.org/pid/13/3935>)
5. Joaquín Huerta, also known as Joaquín Huerta (<https://dblp.org/pid/67/3031>)
6. Joaquín Bedia, also known as Joaquín Bedia (<https://dblp.org/pid/211/6348>)
7. Joaquin Chung 0001, also known as Joaquin Chung (<https://dblp.org/pid/123/3345>)
8. Joaquín Salas, also known as Joaquín Salas (<https://dblp.org/pid/93/2942>)
9. Joaquín Gairín-Sallán, also known as Joaquín Gairín-Sallán (<https://dblp.org/pid/71/8892>)
10. Joaquín Olivares 0001, also known as Joaquín Olivares (<https://dblp.org/pid/86/2422>)

[Assistant] I found the author entity for "Silva-Faundez, Joaquin Alder" as <https://dblp.org/pid/63/10539>. Now I will query the publications authored by this author.

[Tool]
Got 2 rows and 2 columns:
| pub                                                                                | title                                                               |
| ----------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------- |
| Joaquin Alder Silva-Faundez et a...development and research. (2011) (<https://dblp.org/rec/conf/larc/Silva-FaundezFD11>)      | Senor Maderita: A semi-omnidirec...ining, development and research. |
| Joaquin Alder Silva-Faundez et a... Mobile Units Using WSNs. (2015) (<https://dblp.org/rec/journals/ijccc/Silva-FaundezDM15>) | An Anticipatory Control for a Fl...tion of Mobile Units Using WSNs. |

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
SELECT ?pub ?title ?year ?venue WHERE {
  ?pub dblp:authoredBy <https://dblp.org/pid/64/490> .
  ?pub dblp:title ?title .
  ?pub dblp:yearOfPublication ?year .
  ?pub dblp:publishedIn ?venue .
  FILTER ( ?venue IN ( "VTC Spring" , "CoRR" ) )
}
ORDER BY ?year

Mika Hoppari has published the following paper in the venues VTC Spring and CoRR:
- "Dynamic Spectrum Management for European-Wide Research Network" published in VTC Spring in 2020.

No papers were found for Mika Hoppari published in CoRR.

What papers did Hoppari, M. publish in VTC Spring and CoRR?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
dblp at https://qlever.cs.uni-freiburg.de/api/dblp with notes:
1. Use dblp:authoredBy to link publications to authors. The inverse (author -> pubs) is not via dblp:author; queries with dblp:author typically return no results.
2. Publication year is dblp:yearOfPublication (xsd:gYear). Avoid dblp:year. For last N years use YEAR(NOW()) in FILTER; use >= for inclusive bounds. Don’t assume current year in prose. MIN/MAX work on gYear; avoid unnecessary casts.
3. Venue is dblp:publishedIn (string like short name) and/or dblp:publishedInStream (entity IRI for series/journal/conference). For simple venue text, use dblp:publishedIn.
4. To list an author’s publications: SELECT ?pub WHERE { ?pub dblp:authoredBy <authorIRI> }. Then OPTIONAL get dblp:title, dblp:publishedIn, dblp:yearOfPublication.
5. For yes/no authorship checks, use ASK with dblp:authoredBy, e.g., ASK { <pubIRI> dblp:authoredBy <authorIRI> }.
6. Titles are via dblp:title on publication entities. rdfs:label often exists but is less reliable for titles; prefer dblp:title.
7. If dblp:authoredBy on a pub yields a disambiguation author node (e.g., “… (disambiguation)”), treat it as the author IRI to use in joins; it still identifies the creator.
8. Use dblp:createdBy as an alternative to dblp:authoredBy when authoredBy is missing; both link pubs to creators. Prefer authoredBy for authorship semantics.
9. When filtering by venue names, dblp:publishedIn is a short string (e.g., ‘WSC’, ‘ICALT’, ‘Gov. Inf. Q.’). Avoid FILTER on ?pub IRI strings; filter on dblp:publishedIn value.
10. Avoid rdf:type for pubs; rely on authoredBy/title/publishedIn/yearOfPublication. When counting, use COUNT(DISTINCT ?pub). For average per year, take AVG over yearly counts (subquery GROUP BY year); don’t divide by year-span.
11. Avoid using foaf:name/rdfs:label on creators for joins. Creators expose dblp:creatorName/primaryCreatorName and dblp:primaryAffiliation (string). Prefer joins on IRIs; fetch names/affiliations separately. Use SELECT DISTINCT ?author to dedup.
12. When a SELECT returns no rows unexpectedly, check schema via search_property/search_property_of_entity or list the entity. Many failures stem from using wrong props (dblp:author vs dblp:authoredBy).
13. Negations: avoid tautological NOT EXISTS. Prefer ASK { positive pattern } and invert in prose. For “also published in V?”, test other pubs by same authors and exclude the given pub via FILTER(?other != <pubIRI>) together with dblp:publishedIn 'V'.
14. Avoid text search on titles with CONTAINS/LCASE for exact identification; prefer search_entity to get the record IRI, then query structured triples. After search_entity, verify exact title via dblp:title; don’t pick a “closest match” blindly.
15. Be careful with complex ASK + FILTER combinations; QLever may error (CartesianProductJoin assertion). Simplify logic or split into separate queries to avoid engine bugs.
16. For number of authors, prefer dblp:numberOfCreators when available; otherwise COUNT(DISTINCT ?a) over dblp:authoredBy.

General notes for all knowledge graphs:
1. Normalize NL negations to a clear existential query. Prefer ASK { positive pattern }. For negated questions, evaluate the positive fact and invert only in prose. Avoid tautological or heavy NOT EXISTS patterns that can be slow or misleading.
2. For relative time windows (“last N years”), always use YEAR(NOW()) in SPARQL and align inclusive/exclusive bounds with the question phrasing. Do not hardcode current year in answers; base the conclusion strictly on query results.

You can use the following SPARQL prefixes implicitly in all functions:
bibtex: <http://purl.org/net/nknouf/ns/bibtex#
cito: <http://purl.org/spar/cito/
datacite: <http://purl.org/spar/datacite/
dblp: <https://dblp.org/rdf/schema#
dblps: <https://dblp.org/rdf/schema-2020-07-01#
literal: <http://purl.org/spar/literal/
owl: <http://www.w3.org/2002/07/owl#
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
schema: <http://schema.org/
terms: <http://purl.org/dc/terms/
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What papers did Hoppari, M. publish in VTC Spring and CoRR?

[Assistant]
To answer the question about the papers published by Hoppari, M. in the venues "VTC Spring" and "CoRR," I will follow these steps:

1. Search for the author entity corresponding to "Hoppari, M." in the dblp knowledge graph.
2. Query for publications authored by this author.
3. Filter the publications to those published in the venues "VTC Spring" and "CoRR."
4. Retrieve the titles and publication years of these papers.

I will start by searching for the author "Hoppari, M." in the dblp knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Mika Hoppari, also known as Mika Hoppari (<https://dblp.org/pid/64/490>)
2. Mika Hoppari et al.: Performance...nologies-Empirical Study. (2021) (<https://dblp.org/rec/journals/fi/HoppariUMHR21>)
3. Mika Hoppari et al.: The LSA Bas... Commercial MNO Networks. (2020) (<https://dblp.org/rec/conf/eucnc/HoppariHP20>)

[Assistant] I found the author entity for "Mika Hoppari" with the IRI <https://dblp.org/pid/64/490>. Now I will query for publications authored by Mika Hoppari and filter those published in the venues "VTC Spring" and "CoRR." I will retrieve the titles and publication years of these papers.

[Tool]
Got 1 row and 4 columns:
| pub                                                                                | title                                                           | year             | venue      |
| --------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------- | ---------------- | ---------- |
| Ilkka Harjula et al.: Dynamic Sp...an-Wide Research Network. (2020) (<https://dblp.org/rec/conf/vtc/HarjulaPVPHFS20>) | Dynamic Spectrum Management for European-Wide Research Network. | 2020 (xsd:gYear) | VTC Spring |

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
SELECT ( COUNT( DISTINCT ?pub ) AS ?count ) WHERE {
  ?pub dblp:authoredBy <https://dblp.org/pid/21/4802>
}

Kalyanmoy Deb has published 616 papers according to the dblp knowledge graph.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
dblp at https://qlever.cs.uni-freiburg.de/api/dblp with notes:
1. Use dblp:authoredBy to link publications to authors. The inverse (author -> pubs) is not via dblp:author; queries with dblp:author typically return no results.
2. Publication year is dblp:yearOfPublication (xsd:gYear). Avoid dblp:year. For last N years use YEAR(NOW()) in FILTER; use >= for inclusive bounds. Don’t assume current year in prose. MIN/MAX work on gYear; avoid unnecessary casts.
3. Venue is dblp:publishedIn (string like short name) and/or dblp:publishedInStream (entity IRI for series/journal/conference). For simple venue text, use dblp:publishedIn.
4. To list an author’s publications: SELECT ?pub WHERE { ?pub dblp:authoredBy <authorIRI> }. Then OPTIONAL get dblp:title, dblp:publishedIn, dblp:yearOfPublication.
5. For yes/no authorship checks, use ASK with dblp:authoredBy, e.g., ASK { <pubIRI> dblp:authoredBy <authorIRI> }.
6. Titles are via dblp:title on publication entities. rdfs:label often exists but is less reliable for titles; prefer dblp:title.
7. If dblp:authoredBy on a pub yields a disambiguation author node (e.g., “… (disambiguation)”), treat it as the author IRI to use in joins; it still identifies the creator.
8. Use dblp:createdBy as an alternative to dblp:authoredBy when authoredBy is missing; both link pubs to creators. Prefer authoredBy for authorship semantics.
9. When filtering by venue names, dblp:publishedIn is a short string (e.g., ‘WSC’, ‘ICALT’, ‘Gov. Inf. Q.’). Avoid FILTER on ?pub IRI strings; filter on dblp:publishedIn value.
10. Avoid rdf:type for pubs; rely on authoredBy/title/publishedIn/yearOfPublication. When counting, use COUNT(DISTINCT ?pub). For average per year, take AVG over yearly counts (subquery GROUP BY year); don’t divide by year-span.
11. Avoid using foaf:name/rdfs:label on creators for joins. Creators expose dblp:creatorName/primaryCreatorName and dblp:primaryAffiliation (string). Prefer joins on IRIs; fetch names/affiliations separately. Use SELECT DISTINCT ?author to dedup.
12. When a SELECT returns no rows unexpectedly, check schema via search_property/search_property_of_entity or list the entity. Many failures stem from using wrong props (dblp:author vs dblp:authoredBy).
13. Negations: avoid tautological NOT EXISTS. Prefer ASK { positive pattern } and invert in prose. For “also published in V?”, test other pubs by same authors and exclude the given pub via FILTER(?other != <pubIRI>) together with dblp:publishedIn 'V'.
14. Avoid text search on titles with CONTAINS/LCASE for exact identification; prefer search_entity to get the record IRI, then query structured triples. After search_entity, verify exact title via dblp:title; don’t pick a “closest match” blindly.
15. Be careful with complex ASK + FILTER combinations; QLever may error (CartesianProductJoin assertion). Simplify logic or split into separate queries to avoid engine bugs.
16. For number of authors, prefer dblp:numberOfCreators when available; otherwise COUNT(DISTINCT ?a) over dblp:authoredBy.

General notes for all knowledge graphs:
1. Normalize NL negations to a clear existential query. Prefer ASK { positive pattern }. For negated questions, evaluate the positive fact and invert only in prose. Avoid tautological or heavy NOT EXISTS patterns that can be slow or misleading.
2. For relative time windows (“last N years”), always use YEAR(NOW()) in SPARQL and align inclusive/exclusive bounds with the question phrasing. Do not hardcode current year in answers; base the conclusion strictly on query results.

You can use the following SPARQL prefixes implicitly in all functions:
bibtex: <http://purl.org/net/nknouf/ns/bibtex#
cito: <http://purl.org/spar/cito/
datacite: <http://purl.org/spar/datacite/
dblp: <https://dblp.org/rdf/schema#
dblps: <https://dblp.org/rdf/schema-2020-07-01#
literal: <http://purl.org/spar/literal/
owl: <http://www.w3.org/2002/07/owl#
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
schema: <http://schema.org/
terms: <http://purl.org/dc/terms/
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] How many papers has Deb, K. published?

[Assistant] First, I need to find the entity IRI for the author "Deb, K." in the dblp knowledge graph. Then I will count the number of publications authored by this author using the property dblp:authoredBy.

[Tool]
Top 10 entity alternatives:
1. Kalyanmoy Deb, also known as Kalyanmoy Deb (<https://dblp.org/pid/21/4802>)
2. Deb K. Pal, also known as Deb K. Pal (<https://dblp.org/pid/148/4638>)
3. Abhijit K. Deb, also known as Abhijit K. Deb (<https://dblp.org/pid/08/3720>)
4. Sanjib K. Deb, also known as Sanjib K. Deb (<https://dblp.org/pid/65/10889>)
5. S. K. Deb, also known as S. K. Deb (<https://dblp.org/pid/94/6422>)
6. Nirmal K. Deb, also known as Nirmal K. Deb (<https://dblp.org/pid/204/4982>)
7. Parag K. Deb, also known as Parag K. Deb (<https://dblp.org/pid/88/2720>)
8. Rajat K. Deb, also known as Rajat K. Deb (<https://dblp.org/pid/38/2553>)
9. Sudip K. Deb, also known as Sudip K. Deb (<https://dblp.org/pid/316/6127>)
10. Sumanta K. Deb, also known as Sumanta K. Deb (<https://dblp.org/pid/201/5654>)

[Assistant] The most likely author "Deb, K." is Kalyanmoy Deb with the IRI <https://dblp.org/pid/21/4802>. I will now count the number of publications authored by Kalyanmoy Deb using this IRI.

[Tool]
Got 1 row and 1 column:
| count         |
| ------------- |
| 616 (xsd:int) |

[Tool] Stopped generation process