PREFIX dblp: <https://dblp.org/rdf/schema#>
SELECT ?pub ?title ?year WHERE {
  ?pub dblp:authoredBy <https://dblp.org/pid/s/RichardEdwinStearns> .
  ?pub dblp:title ?title .
  ?pub dblp:yearOfPublication ?year .
  FILTER ( ?year >= YEAR( NOW () ) - 3 )
}
ORDER BY DESC ( ?year )

Richard E. Stearns has not published any papers in the last 3 years according to the dblp knowledge graph.

Which papers did the author Richard E. Stearns publish in the last 3 years?

[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 Richard E. Stearns publish in the last 3 years?

[Assistant] To answer the question about which papers Richard E. Stearns published in the last 3 years, I will first search for the author entity for "Richard E. Stearns" in the dblp knowledge graph. Then, I will query for publications authored by this entity with a publication year within the last 3 years.

[Tool]
Top 10 entity alternatives:
1. Richard Edwin Stearns, also known as Richard Edwin Stearns (<https://dblp.org/pid/s/RichardEdwinStearns>)
2. E. Richard, also known as E. Richard (<https://dblp.org/pid/145/1512>)
3. Richard E. Edwards, also known as Richard E. Edwards (<https://dblp.org/pid/89/9799>)
4. Richard E. Ewing, also known as Richard E. Ewing (<https://dblp.org/pid/43/6972>)
5. Richard E. Ladner, also known as Richard E. Ladner (<https://dblp.org/pid/l/RELadner>)
6. Richard E. Jones, also known as Richard E. Jones (<https://dblp.org/pid/j/RichardJones>)
7. Richard E. Crandall, also known as Richard E. Crandall (<https://dblp.org/pid/c/RichardECrandall>)
8. Richard Evans 0003, also known as Richard Evans (<https://dblp.org/pid/78/9937>)
9. Richard E. Carson, also known as Richard E. Carson (<https://dblp.org/pid/46/6520>)
10. Richard Ehrenborg, also known as Richard Ehrenborg (<https://dblp.org/pid/91/3911>)

[Assistant] I found the author entity for Richard E. Stearns as <https://dblp.org/pid/s/RichardEdwinStearns>. Now I will query for the papers authored by Richard E. Stearns published in the last 3 years. I will use the property dblp:authoredBy to link publications to the author and filter by the publication year using dblp:yearOfPublication.

[Tool] Got no rows and 3 columns

[Assistant] There are no papers authored by Richard E. Stearns published in the last 3 years in the dblp knowledge graph. I will now provide this as the final answer.

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
ASK {
  <https://dblp.org/rec/journals/jips/WangG19> dblp:authoredBy ?author .
  FILTER ( ?author IN ( <https://dblp.org/pid/05/6300-2> , <https://dblp.org/pid/122/3626-1> , <https://dblp.org/pid/90/343> ) )
}

No, the authors of the paper 'Benchmarking and Analyzing Point Cloud Classification under Corruptions' have not published the paper 'An Evolution Model of Rumor Spreading Based on WeChat Social Circle'.

Have the authors of the paper 'Benchmarking and Analyzing Point Cloud Classification under Corruptions' not not published the paper 'An Evolution Model of Rumor Spreading Based on WeChat Social Circle'?

[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] Have the authors of the paper 'Benchmarking and Analyzing Point Cloud Classification under Corruptions' not not published the paper 'An Evolution Model of Rumor Spreading Based on WeChat Social Circle'?

[Assistant]
The user question is a double negation: "Have the authors of paper A not not published paper B?" which simplifies to "Have the authors of paper A published paper B?"

Step 1: Identify the two papers by their titles:
- Paper A: "Benchmarking and Analyzing Point Cloud Classification under Corruptions"
- Paper B: "An Evolution Model of Rumor Spreading Based on WeChat Social Circle"

Step 2: Find the IRIs of these two papers in dblp by searching for their exact titles.

Step 3: Find the authors of paper A.

Step 4: Check if any of these authors have authored paper B.

If yes, answer "Yes", else "No".

I will start by searching for the entity IRIs of the two papers by their titles.

[Tool]
Top 10 entity alternatives:
1. Jiawei Ren et al.: Benchmarking ...cation under Corruptions. (2022) (<https://dblp.org/rec/conf/icml/RenP022>)
2. Jiawei Ren et al.: Benchmarking ...cation under Corruptions. (2022) (<https://dblp.org/rec/journals/corr/abs-2202-03377>)
3. Zhiqiang Tian et al.: Joint grap...ness against corruptions. (2023) (<https://dblp.org/rec/journals/isci/TianLHD23>)
4. Qiufan Ji et al.: Benchmarking a...ing Adversarial Examples. (2023) (<https://dblp.org/rec/conf/iccv/JiWSHC023>)
5. Qiufan Ji et al.: Benchmarking a...ing Adversarial Examples. (2023) (<https://dblp.org/rec/journals/corr/abs-2307-16361>)
6. Abdurrahman Hazer and Remzi Yild...int Cloud Classification. (2025) (<https://dblp.org/rec/journals/access/HazerY25>)
7. Rajat K. Doshi: Leveraging Point...Classification Challenge. (2024) (<https://dblp.org/rec/journals/corr/abs-2404-18665>)
8. Li Ling et al.: Benchmarking Cla...Point Cloud Registration. (2024) (<https://dblp.org/rec/conf/icra/LingZBFW24>)
9. Lei Zhu et al.: Curvature-Variat...ication and Segmentation. (2022) (<https://dblp.org/rec/journals/spl/ZhuCLHG22>)
10. Li Ling et al.: Benchmarking Cla...Point Cloud Registration. (2024) (<https://dblp.org/rec/journals/corr/abs-2405-06279>)

[Assistant]
I found two records for the paper "Benchmarking and Analyzing Point Cloud Classification under Corruptions" from 2022:
- https://dblp.org/rec/conf/icml/RenP022
- https://dblp.org/rec/journals/corr/abs-2202-03377

I will now search for the second paper "An Evolution Model of Rumor Spreading Based on WeChat Social Circle" to find its IRI.

[Tool]
Top 10 entity alternatives:
1. Lubang Wang and Yue Guo: An Evol... on WeChat Social Circle. (2019) (<https://dblp.org/rec/journals/jips/WangG19>)
2. An Lu et al.: An Evolution Model...ent Theory (August 2018). (2018) (<https://dblp.org/rec/journals/access/LuDLGJC18>)
3. Yaghoob Naimi and Mohammad Naimi...n complex social networks (2013) (<https://dblp.org/rec/journals/corr/abs-1303-6120>)
4. Jie Liu et al.: Analysis of Rumo...d SIR Model in Microblog. (2014) (<https://dblp.org/rec/conf/aimsa/LiuNHL14>)
5. Chaitanya Kaligotla et al.: An a...ractions on social media. (2015) (<https://dblp.org/rec/conf/wsc/KaligotlaYC15a>)
6. Chaitanya Kaligotla et al.: An a...ractions on social media. (2015) (<https://dblp.org/rec/conf/wsc/KaligotlaYC15>)
7. Jinxian Li et al.: Rumor Spreadi...lity Generating Function. (2019) (<https://dblp.org/rec/journals/complexity/LiHJ19>)
8. Xiaolong Li and Deyang Zhang: Th... Similarity of Community. (2017) (<https://dblp.org/rec/conf/3pgcic/LiZ17>)
9. Jianye Yu et al.: Analysis of Co... Evolutionary Game Model. (2012) (<https://dblp.org/rec/conf/cgc/YuWLSC12>)
10. Jinlong Fu et al.: Rumor Spreadi...and Information Overload. (2023) (<https://dblp.org/rec/journals/access/FuSF23>)

[Assistant]
I found a record for the paper "An Evolution Model of Rumor Spreading Based on WeChat Social Circle" from 2019:
- https://dblp.org/rec/journals/jips/WangG19

Next, I will find the authors of the first paper "Benchmarking and Analyzing Point Cloud Classification under Corruptions" using the first IRI https://dblp.org/rec/conf/icml/RenP022.

[Tool]
Got 3 rows and 1 column:
| author                                              |
| --------------------------------------------------- |
| Ziwei Liu 0002 (<https://dblp.org/pid/05/6300-2>)   |
| Jiawei Ren 0001 (<https://dblp.org/pid/122/3626-1>) |
| Liang Pan (<https://dblp.org/pid/90/343>)           |

[Assistant]
The authors of the paper "Benchmarking and Analyzing Point Cloud Classification under Corruptions" are:
- Ziwei Liu (https://dblp.org/pid/05/6300-2)
- Jiawei Ren (https://dblp.org/pid/122/3626-1)
- Liang Pan (https://dblp.org/pid/90/343)

Now I will check if any of these authors have authored the paper "An Evolution Model of Rumor Spreading Based on WeChat Social Circle" (https://dblp.org/rec/journals/jips/WangG19).

[Tool] False

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
ASK WHERE {
  <https://dblp.org/rec/conf/sis/RamonMMA09> dblp:authoredBy ?author1 , ?author2 .
  ?author1 dblp:creatorName ?name1 .
  ?author2 dblp:creatorName ?name2 .
  FILTER ( CONTAINS( LCASE( ?name1 ) , "fernando m" ) && CONTAINS( LCASE( ?name2 ) , "ramón" ) || CONTAINS( LCASE( ?name1 ) , "ramón" ) && CONTAINS( LCASE( ?name2 ) , "fernando m" ) )
}

The paper 'A Model Driven Approach for Generating Code from Security Requirements' has Fernando M. (Fernando Molina) and Ramón, . Sánchez (Óscar Sánchez Ramón) as co-authors, so they have co-authored the paper.

Have Fernando M. and Ram\u00F3n, \. S\u00E1nchez not co-authored the paper 'A Model Driven Approach for Generating Code from Security Requirements'?

[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] Have Fernando M. and Ram\u00F3n, \. S\u00E1nchez not co-authored the paper 'A Model Driven Approach for Generating Code from Security Requirements'?

[Assistant]
To answer this question, I need to verify if the paper titled "A Model Driven Approach for Generating Code from Security Requirements" has both Fernando M. and Ramón, . Sánchez as co-authors.

Step 1: Search for the paper by its exact title to get its publication IRI.
Step 2: Check the authors of this paper to see if both Fernando M. and Ramón, . Sánchez are listed as authors.
Step 3: Based on the authorship, answer whether they have co-authored the paper or not.

I will start by searching for the paper by its title.

[Tool]
Top 10 entity alternatives:
1. Óscar Sánchez Ramón et al.: A Mo...om Security Requirements. (2009) (<https://dblp.org/rec/conf/sis/RamonMMA09>)
2. José Cordeiro: A Model Driven Sy...servable Actions to Code. (2017) (<https://dblp.org/rec/conf/bmsd/Cordeiro17>)
3. Christoforos Zolotas et al.: Fro...for RESTful web services. (2017) (<https://dblp.org/rec/journals/ase/ZolotasDCS17>)
4. Isabel Sofia Brito et al.: From ...ontroller implementation. (2016) (<https://dblp.org/rec/conf/indin/BritoB016>)
5. Umair Sabir et al.: A Model Driv...ls From Java Source Code. (2019) (<https://dblp.org/rec/journals/access/SabirAHABA19>)
6. Audris Kalnins et al.: From Requ...de in a Model Driven Way. (2009) (<https://dblp.org/rec/conf/adbis/KalninsKCS09>)
7. Linzhang Wang et al.: A Threat M...ach for Security Testing. (2007) (<https://dblp.org/rec/conf/icse/WangWX07>)
8. Oscar Pastor and Marcela Ruiz: F...tware Production Process. (2018) (<https://dblp.org/rec/journals/emisaij/PastorR18>)
9. Cícero A. G. Araújo: A model for... code from multiple GUIs. (2022) (<https://dblp.org/rec/conf/kbse/Araujo22>)
10. Chiara Braghin et al.: A Model D...ity Scenarios Deployment. (2019) (<https://dblp.org/rec/conf/esorics/BraghinCDFMR19>)

[Assistant] I found a paper titled "A Model Driven Approach for Generating Code from Security Requirements" authored by Óscar Sánchez Ramón et al. in 2009 with the IRI <https://dblp.org/rec/conf/sis/RamonMMA09>. Now I will check the authors of this paper to see if both Fernando M. and Ramón, . Sánchez are listed as authors.

[Tool]
Got 6 rows and 2 columns:
| author                                                       | name                        |
| ------------------------------------------------------------ | --------------------------- |
| José Ambrosio Toval Álvarez (<https://dblp.org/pid/06/3929>) | Ambrosio Toval              |
| José Ambrosio Toval Álvarez (<https://dblp.org/pid/06/3929>) | José Ambrosio Toval Álvarez |
| Fernando Molina (<https://dblp.org/pid/15/2623>)             | Fernando Molina             |
| Óscar Sánchez Ramón (<https://dblp.org/pid/46/7849>)         | Óscar Sánchez Ramón         |
| Jesús García Molina (<https://dblp.org/pid/78/4516>)         | Jesús García Molina         |
| Jesús García Molina (<https://dblp.org/pid/78/4516>)         | Jesús Joaquín García Molina |

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
SELECT ?pub ?title WHERE {
  ?pub dblp:authoredBy <https://dblp.org/pid/199/9664> .
  OPTIONAL {
    ?pub dblp:title ?title
  }
}

Got 10 rows and 2 columns:
| pub                                                                                | title                                                               |
| ------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------- |
| Loukmen Regainia et al.: A class... fix software weaknesses. (2016) (<https://dblp.org/rec/conf/aiccsa/RegainiaSE16>)     | A classification methodology for...to help fix software weaknesses. |
| Sébastien Salva and Loukmen Rega...More Secure Applications. (2017) (<https://dblp.org/rec/conf/crisis/SalvaR17>)         | Using Data Integration to Help Design More Secure Applications.     |
| Loukmen Regainia and Sébastien S...-Defense Tree Generation. (2017) (<https://dblp.org/rec/conf/icissp/RegainiaS17>)      | A Methodology of Security Patter... Attack-Defense Tree Generation. |
| Sébastien Salva and Loukmen Rega...ased on Data Integration. (2017) (<https://dblp.org/rec/conf/icissp/SalvaR17>)         | A Security Pattern Classification Based on Data Integration.        |
| Sébastien Salva and Loukmen Rega...ion for Security Testing. (2017) (<https://dblp.org/rec/conf/pts/SalvaR17>)            | Using Data Integration for Security Testing.                        |
| Sébastien Salva and Loukmen Rega...ing their Implementation. (2020) (<https://dblp.org/rec/journals/corr/abs-2007-03275>) | An Advanced Approach for Choosin...d Checking their Implementation. |
| Sébastien Salva and Loukmen Rega...sign secure applications. (2019) (<https://dblp.org/rec/journals/jcs/SalvaR19>)        | A catalogue associating security...s to design secure applications. |
| Sébastien Salva and Loukmen Rega...n of concrete test cases. (2019) (<https://dblp.org/rec/journals/sqj/SalvaR19>)        | An approach for guiding develope...neration of concrete test cases. |
| Loukmen Regainia et al.: Une dém... des patrons de sécurité. (2016) (<https://dblp.org/rec/journals/tsi/RegainiaSB16>)    | Une démarche pour l'assistance à...isation des patrons de sécurité. |
| Loukmen Regainia: Assisting in s...applications sécurisées). (2018) (<https://dblp.org/rec/phd/hal/Regainia18>)           | Assisting in secure application ...test d'applications sécurisées). |

Loukmen Regainia wrote the following publications:
1. A classification methodology for security patterns to help fix software weaknesses (2016)
2. Using Data Integration to Help Design More Secure Applications (2017)
3. A Methodology of Security Pattern Classification for Attack-Defense Tree Generation (2017)
4. A Security Pattern Classification Based on Data Integration (2017)
5. Using Data Integration for Security Testing (2017)
6. An Advanced Approach for Choosing and Checking their Implementation (2020)
7. A catalogue associating security patterns to design secure applications (2019)
8. An approach for guiding developers in the generation of concrete test cases (2019)
9. Une démarche pour l'assistance à la formalisation des patrons de sécurité (2016)
10. Assisting in secure application testing (2018)

Which publications did Loukmen Regainia 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 publications did Loukmen Regainia write?

[Assistant]
To answer the question about which publications Loukmen Regainia wrote, I need to find the entity representing Loukmen Regainia in the dblp knowledge graph and then query for publications authored by this entity using the property dblp:authoredBy.

Step 1: Search for the entity Loukmen Regainia in dblp.

[Tool]
Top 10 entity alternatives:
1. Loukmen Regainia, also known as Loukmen Regainia (<https://dblp.org/pid/199/9664>)
2. Sébastien Salva and Loukmen Rega...ion for Security Testing. (2017) (<https://dblp.org/rec/conf/pts/SalvaR17>)
3. Sébastien Salva and Loukmen Rega...ased on Data Integration. (2017) (<https://dblp.org/rec/conf/icissp/SalvaR17>)
4. Loukmen Regainia et al.: Une dém... des patrons de sécurité. (2016) (<https://dblp.org/rec/journals/tsi/RegainiaSB16>)
5. Sébastien Salva and Loukmen Rega...More Secure Applications. (2017) (<https://dblp.org/rec/conf/crisis/SalvaR17>)
6. Loukmen Regainia et al.: A class... fix software weaknesses. (2016) (<https://dblp.org/rec/conf/aiccsa/RegainiaSE16>)
7. Loukmen Regainia and Sébastien S...-Defense Tree Generation. (2017) (<https://dblp.org/rec/conf/icissp/RegainiaS17>)
8. Sébastien Salva and Loukmen Rega...ing their Implementation. (2020) (<https://dblp.org/rec/journals/corr/abs-2007-03275>)
9. Sébastien Salva and Loukmen Rega...sign secure applications. (2019) (<https://dblp.org/rec/journals/jcs/SalvaR19>)
10. Loukmen Regainia: Assisting in s...applications sécurisées). (2018) (<https://dblp.org/rec/phd/hal/Regainia18>)

[Assistant] I found the entity for Loukmen Regainia in dblp with the IRI <https://dblp.org/pid/199/9664>. Now I will query for publications authored by Loukmen Regainia using this IRI.

[Tool]
Got 10 rows and 2 columns:
| pub                                                                                | title                                                               |
| ------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------- |
| Loukmen Regainia et al.: A class... fix software weaknesses. (2016) (<https://dblp.org/rec/conf/aiccsa/RegainiaSE16>)     | A classification methodology for...to help fix software weaknesses. |
| Sébastien Salva and Loukmen Rega...More Secure Applications. (2017) (<https://dblp.org/rec/conf/crisis/SalvaR17>)         | Using Data Integration to Help Design More Secure Applications.     |
| Loukmen Regainia and Sébastien S...-Defense Tree Generation. (2017) (<https://dblp.org/rec/conf/icissp/RegainiaS17>)      | A Methodology of Security Patter... Attack-Defense Tree Generation. |
| Sébastien Salva and Loukmen Rega...ased on Data Integration. (2017) (<https://dblp.org/rec/conf/icissp/SalvaR17>)         | A Security Pattern Classification Based on Data Integration.        |
| Sébastien Salva and Loukmen Rega...ion for Security Testing. (2017) (<https://dblp.org/rec/conf/pts/SalvaR17>)            | Using Data Integration for Security Testing.                        |
| Sébastien Salva and Loukmen Rega...ing their Implementation. (2020) (<https://dblp.org/rec/journals/corr/abs-2007-03275>) | An Advanced Approach for Choosin...d Checking their Implementation. |
| Sébastien Salva and Loukmen Rega...sign secure applications. (2019) (<https://dblp.org/rec/journals/jcs/SalvaR19>)        | A catalogue associating security...s to design secure applications. |
| Sébastien Salva and Loukmen Rega...n of concrete test cases. (2019) (<https://dblp.org/rec/journals/sqj/SalvaR19>)        | An approach for guiding develope...neration of concrete test cases. |
| Loukmen Regainia et al.: Une dém... des patrons de sécurité. (2016) (<https://dblp.org/rec/journals/tsi/RegainiaSB16>)    | Une démarche pour l'assistance à...isation des patrons de sécurité. |
| Loukmen Regainia: Assisting in s...applications sécurisées). (2018) (<https://dblp.org/rec/phd/hal/Regainia18>)           | Assisting in secure application ...test d'applications sécurisées). |

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
ASK {
  <https://dblp.org/rec/journals/jsw/LiuLCGY09> dblp:authoredBy <https://dblp.org/pid/52/1471>
}

No, the author Xue-Bin Liang of the paper 'A complete proof of global exponential convergence of a neural network for quadratic optimization with bound constraints' did not publish the paper 'Application of Genetic Algorithms for a Tyre Production Scheduling Information System'.

Didn't the authors of the paper 'A complete proof of global exponential convergence of a neural network for quadratic optimization with bound constraints' publish 'Application of Genetic Algorithms for a Tyre Production Scheduling Information 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] Didn't the authors of the paper 'A complete proof of global exponential convergence of a neural network for quadratic optimization with bound constraints' publish 'Application of Genetic Algorithms for a Tyre Production Scheduling Information System'?

[Assistant]
To answer this question, I need to:

1. Find the paper "A complete proof of global exponential convergence of a neural network for quadratic optimization with bound constraints" in the dblp knowledge graph.
2. Retrieve the authors of this paper.
3. Check if any of these authors also published the paper "Application of Genetic Algorithms for a Tyre Production Scheduling Information System".

I will start by searching for the first paper to get its IRI and then find its authors.

[Tool]
Top 10 entity alternatives:
1. Xue-Bin Liang: A complete proof ...n with bound constraints. (2001) (<https://dblp.org/rec/journals/tnn/Liang01>)
2. María José Pérez-Ilzarbe: Conver...n with bound constraints. (1998) (<https://dblp.org/rec/journals/tnn/Perez-Ilzarbe98>)
3. María José Pérez-Ilzarbe: Improv...neral linear constraints. (2014) (<https://dblp.org/rec/journals/ijon/Perez-Ilzarbe14>)
4. Kay Chen Tan et al.: Global expo...d quadratic optimization. (2004) (<https://dblp.org/rec/journals/ijon/TanTY04>)
5. Yongqing Yang et al.: A Neural N...tic Equality Constraints. (2005) (<https://dblp.org/rec/conf/isnn/YangCZ05>)
6. Abdesselam Bouzerdoum and Tim R....n with bound constraints. (1993) (<https://dblp.org/rec/journals/tnn/BouzerdoumP93>)
7. Mauro Forti et al.: Global expon...works with infinite gain. (2005) (<https://dblp.org/rec/journals/tnn/FortiNP05>)
8. Xing-Bao Gao et al.: A neural ne...roblems with constraints. (2004) (<https://dblp.org/rec/journals/tnn/GaoLX04>)
9. Andrei Kanavalau and Sanjay Lall...Training Neural Networks. (2024) (<https://dblp.org/rec/conf/ccta/KanavalauL24>)
10. Wenjing Li et al.: Projected Neu... With Linear Constraints. (2020) (<https://dblp.org/rec/journals/tnn/LiBX20>)

[Assistant] I found the paper "A complete proof of global exponential convergence of a neural network for quadratic optimization with bound constraints" authored by Xue-Bin Liang in 2001 with the IRI <https://dblp.org/rec/journals/tnn/Liang01>. Now I will retrieve the authors of this paper.

[Tool]
Got 1 row and 1 column:
| author                                         |
| ---------------------------------------------- |
| Xue-Bin Liang (<https://dblp.org/pid/52/1471>) |

[Assistant] The author of the paper "A complete proof of global exponential convergence of a neural network for quadratic optimization with bound constraints" is Xue-Bin Liang. Now I will check if Xue-Bin Liang also published the paper "Application of Genetic Algorithms for a Tyre Production Scheduling Information System". I will search for this second paper in the dblp knowledge graph to get its IRI.

[Tool]
Top 10 entity alternatives:
1. Lin Liu et al.: Application of G...uling Information System. (2009) (<https://dblp.org/rec/journals/jsw/LiuLCGY09>)
2. Anas Neumann et al.: Genetic alg...ion: a systematic review. (2024) (<https://dblp.org/rec/journals/ijpr/NeumannHRP24>)
3. Jens Hartmann et al.: A Genetic ...on and Transport Systems. (2012) (<https://dblp.org/rec/conf/or/HartmannMFS12>)
4. Johannes Hintsch et al.: An info... of application services. (2018) (<https://dblp.org/rec/journals/isem/HintschKT18>)
5. Mohsen Rostamian Delavar et al.:...n and air transportation. (2010) (<https://dblp.org/rec/journals/eswa/DelavarHM10>)
6. A. Serengul Guven Smith and Ann ...based Information System. (2003) (<https://dblp.org/rec/journals/aiedu/SmithB03>)
7. Adebayo Abayomi-Alli et al.: Hyb...Nurse Scheduling Systems. (2022) (<https://dblp.org/rec/journals/ijssmet/AbayomiAlliUMAA22>)
8. Tomoki Shibata et al.: Generaliz...uction Scheduling System. (2007) (<https://dblp.org/rec/conf/case/ShibataZHSF07>)
9. An Application of Chromatic Prot...versal Information System (2007) (<https://dblp.org/rec/journals/corr/abs-0708-0598>)
10. Tadeusz Lasota et al.: Applicati...for a Regression Problem. (2014) (<https://dblp.org/rec/conf/iccci/LasotaSTTT14>)

[Assistant] I found the paper "Application of Genetic Algorithms for a Tyre Production Scheduling Information System" authored by Lin Liu et al. in 2009 with the IRI <https://dblp.org/rec/journals/jsw/LiuLCGY09>. Now I will check if Xue-Bin Liang is one of the authors of this paper.

[Tool] False

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
ASK WHERE {
  <https://dblp.org/rec/conf/itc/DintemanB93> dblp:authoredBy ?author .
  FILTER ( ?author IN ( <https://dblp.org/pid/17/2361> , <https://dblp.org/pid/205/0735> , <https://dblp.org/pid/22/2298> , <https://dblp.org/pid/77/4903> ) )
}

The authors of the paper 'A Unifying Approach to Robust Convex Infinite Optimization Duality' have not published the paper 'Differential Virtual Instrumentation with Continuously.'

Have the authors of the paper 'A Unifying Approach to Robust Convex Infinite Optimization Duality' not not published the paper 'Differential Virtual Instrumentation with Continuously'?

[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] Have the authors of the paper 'A Unifying Approach to Robust Convex Infinite Optimization Duality' not not published the paper 'Differential Virtual Instrumentation with Continuously'?

[Assistant]
The question asks if the authors of the paper "A Unifying Approach to Robust Convex Infinite Optimization Duality" have published the paper "Differential Virtual Instrumentation with Continuously." The double negation "not not" means we want to check if they have indeed published the second paper.

Step 1: Identify the paper "A Unifying Approach to Robust Convex Infinite Optimization Duality" in the dblp knowledge graph and get its authors.

Step 2: Identify the paper "Differential Virtual Instrumentation with Continuously" in the dblp knowledge graph.

Step 3: Check if any of the authors of the first paper are authors of the second paper.

I will start by searching for the paper "A Unifying Approach to Robust Convex Infinite Optimization Duality" to get its IRI.

[Tool]
Top 10 entity alternatives:
1. Nguyen Dinh et al.: A Unifying A...ite Optimization Duality. (2017) (<https://dblp.org/rec/journals/jota/DinhGCV17>)
2. Yongfang Cheng et al.: A convex ...mental matrix estimation. (2015) (<https://dblp.org/rec/conf/cvpr/ChengLCS15>)
3. Sattar Vakili et al.: Stochastic...stic Convex Optimization. (2019) (<https://dblp.org/rec/conf/allerton/VakiliS019>)
4. Miguel A. Goberna and Michel Vol...ization on linear spaces. (2022) (<https://dblp.org/rec/journals/ol/GobernaV22a>)
5. Xinyi Le and Jun Wang: A neurody... on convex reformulation. (2014) (<https://dblp.org/rec/conf/IEEEcca/LeW14>)
6. Alexander Shapiro: A dynamic pro...able robust optimization. (2011) (<https://dblp.org/rec/journals/orl/Shapiro11>)
7. Alireza Karimi and Christoph Kam...s by convex optimization. (2017) (<https://dblp.org/rec/journals/automatica/KarimiK17>)
8. Insoon Yang: A Convex Optimizati...ith Wasserstein Distance. (2017) (<https://dblp.org/rec/journals/csysl/Yang17>)
9. Anna Scampicchio and Gianluigi P...x approach to robust LQR. (2020) (<https://dblp.org/rec/conf/cdc/ScampicchioP20>)
10. Alberto Greco et al.: cvxEDA: A ...rmal Activity Processing. (2016) (<https://dblp.org/rec/journals/tbe/GrecoVLSC16>)

[Assistant] I found the paper "A Unifying Approach to Robust Convex Infinite Optimization Duality" with the IRI <https://dblp.org/rec/journals/jota/DinhGCV17>. Next, I will search for the paper "Differential Virtual Instrumentation with Continuously" to get its IRI.

[Tool]
Top 10 entity alternatives:
1. Bryan J. Dinteman and Paul Botsf...tation with Continuously. (1993) (<https://dblp.org/rec/conf/itc/DintemanB93>)
2. Nicolas Grislain: RAG with Differential Privacy. (2024) (<https://dblp.org/rec/journals/corr/abs-2412-19291>)
3. Justine Cassell: Learning with Virtual Peers. (2005) (<https://dblp.org/rec/conf/aied/Cassell05>)
4. Janez Brest: Differential Evolution with Self-Adaptation. (2009) (<https://dblp.org/rec/reference/ai/Brest09>)
5. M. M. Ali: Differential evolutio...eneralized differentials. (2011) (<https://dblp.org/rec/journals/jcam/Ali11>)
6. Tim Clark: Virtual Private Networks with QoS. (2000) (<https://dblp.org/rec/journals/isjgp/Clark00>)
7. Kai Yao: Uncertain differential equation with jumps. (2015) (<https://dblp.org/rec/journals/soco/Yao15>)
8. Herbert Edelsbrunner: Surface Ti...th Differential Topology. (2005) (<https://dblp.org/rec/conf/sgp/Edelsbrunner05>)
9. Atsushi Ohnishi: Classifying Sce...th Differential Scenario. (2008) (<https://dblp.org/rec/conf/jckbse/Ohnishi08>)
10. Erik Ernst: Reconciling Virtual Classes with Genericity. (2006) (<https://dblp.org/rec/conf/jmlc/Ernst06>)

[Assistant] I found the paper "Differential Virtual Instrumentation with Continuously" with the IRI <https://dblp.org/rec/conf/itc/DintemanB93>. Now I will get the authors of the first paper and check if any of them are authors of the second paper.

[Tool]
Got 4 rows and 1 column:
| author1                                              |
| ---------------------------------------------------- |
| Miguel A. Goberna (<https://dblp.org/pid/17/2361>)   |
| Nguyen Dinh (<https://dblp.org/pid/205/0735>)        |
| Michel Volle (<https://dblp.org/pid/22/2298>)        |
| Marco A. López 0001 (<https://dblp.org/pid/77/4903>) |

[Assistant] The authors of the paper "A Unifying Approach to Robust Convex Infinite Optimization Duality" are Miguel A. Goberna, Nguyen Dinh, Michel Volle, and Marco A. López. Now I will check if any of these authors have authored the paper "Differential Virtual Instrumentation with Continuously."

[Tool] False

[Tool] Stopped generation process


PREFIX dblp: <https://dblp.org/rdf/schema#>
SELECT ?year WHERE {
  <https://dblp.org/rec/conf/ecis/CzapH95> dblp:yearOfPublication ?year
}

The publication 'Organizational modelling in distributed corporations' was published in the year 1995.

When was 'Organizational modelling in distributed corporations' 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] When was 'Organizational modelling in distributed corporations' published?

[Assistant] To answer the question about the publication year of "Organizational modelling in distributed corporations," I will first search for the entity (publication) with this exact title in the dblp knowledge graph. Then I will retrieve its year of publication.

[Tool]
Top 10 entity alternatives:
1. Hans Czap and Jörg Haas: Organiz...distributed corporations. (1995) (<https://dblp.org/rec/conf/ecis/CzapH95>)
2. Stanislaw Chrobot: Modelling Com...n in Distributed Systems. (2002) (<https://dblp.org/rec/conf/parelec/Chrobot02>)
3. Richard O. Sinnott: Modelling Dy...ributed Systems in LOTOS. (1999) (<https://dblp.org/rec/conf/fbt/Sinnott99>)
4. Phil Stocks et al.: Modelling open distributed systems in Z. (1992) (<https://dblp.org/rec/journals/comcom/StocksRCL92>)
5. Paolo Masci et al.: Modelling Di...Cognition Systems in PVS. (2011) (<https://dblp.org/rec/journals/eceasst/MasciCBF11>)
6. Weiliang Zhao et al.: Modelling ...Distributed Environments. (2004) (<https://dblp.org/rec/conf/trustbus/ZhaoVB04>)
7. Gabrielle Anderson et al.: Utili...ibuted Systems Modelling. (2013) (<https://dblp.org/rec/journals/corr/AndersonCP13>)
8. Gabrielle Anderson et al.: Utili...ibuted Systems Modelling. (2013) (<https://dblp.org/rec/conf/tark/AndersonCP13>)
9. Anna Yun-Wen Liu: Modelling Dyna...stem Structures in PARSE. (1996) (<https://dblp.org/rec/conf/pdp/Liu96>)
10. Irina A. Lomazova: Interacting A...ling Distributed Systems. (2003) (<https://dblp.org/rec/conf/iccS/Lomazova03>)

[Assistant] I found a publication titled "Organizational modelling in distributed corporations" authored by Hans Czap and Jörg Haas from 1995 with the IRI <https://dblp.org/rec/conf/ecis/CzapH95>. Now I will query the year of publication for this publication.

[Tool]
Got 1 row and 1 column:
| year             |
| ---------------- |
| 1995 (xsd:gYear) |

[Tool] Stopped generation process