PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?painting ?label WHERE {
  ?painting wdt:P31 wd:Q3305213 ; wdt:P195 wd:Q812285 .
  ?painting rdfs:label ?label .
  FILTER ( LANG( ?label ) = "de" ) .
  FILTER ( STRENDS( ?label , ")" ) )
}

Using entities:
- painting (wd:Q3305213), also known as painting (object), paintings: is instance of type of work of art / is subclass of two-dimensional visual artwork / is subclass of work of art / is subclass of Work of art / surface artistically covered with paint / visual artwork, surface artistically covered with paint / visual artwork, surface artistically covered with paint
- Bavarian State Painting Collections (wd:Q812285), also known as Bayerische Staatsgemäldesammlungen, BStGS, Centralgemäldegaleriedirektion: is instance of art gallery / is instance of art museum / is instance of Art museum / is instance of art collection / artworks held by the Free State of Bavaria for Alte Pinakothek, Aschaffenburg, Bamberg, Bayreuth, Schleissheim and others

Using properties:
- collection (wd:P195 as wdt), also known as archival holdings, archives, art collection, bibliographic collection, book collection, etc.: is subproperty of part of / art, museum, archival, or bibliographic collection of which the subject is part / art, museum, archival, or bibliographic collection of which the subject is part
- instance of (wd:P31 as wdt), also known as example of, has type, is a, is an, is of type, etc.: that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform) / type to which this subject corresponds/belongs. Different ... and the volcano is a type (instance) of volcanic landform

Got 2,363 rows and 2 columns, showing the first 5 and last 5 rows below:
| painting                                       | label                                                                                |
| ---------------------------------------------- | ----------------------------------------------------------------------------------------------------------------- |
| Martyrdom of the Theban Legion (wd:Q101150344) | Martyrium der thebaischen Legion / Tod des hl. Gereon (Vorderseite: Hll. Stephanus und Mauritius) (lang:de)       |
| Martyrdom of the Theban Legion (wd:Q101153651) | Martyrium der thebaischen Legion (Vorderseite: Hll. Anno und Gregor der Mohr) (lang:de)                           |
| wd:Q111797391                                  | Maiabend (Nach dem Gewitter) (lang:de)                                                                            |
| wd:Q111798649                                  | Carona (Tessin) (lang:de)                                                                                |
| Abstract Head (pink lips) (wd:Q111798743)      | Abstrakter Kopf (Rosa Lippen) (lang:de)                                                                           |
| ...                                            | ...                                                                                |
| wd:Q62993550                                   | Bildnis des Peter Philipp von Dernbach, Fürstbischof von Bamberg und Würzburg (1619-1683) (lang:de)               |
| wd:Q62994594                                   | Kardinal Benedetto Odescalchi (1611 - 1689) (lang:de)                                                             |
| wd:Q62994788                                   | Kinderbildnis des Alexander Sigismund von Pfalz-Neuburg (1663-1737) (lang:de)                                     |
| wd:Q62999399                                   | Friedrich I. der Siegreiche, Pfalzgraf bei Rhein, Herzog von Bayern, Kurfürst von der Pfalz (1425-1476) (lang:de) |
| wd:Q63106949                                   | Bildnis des Herzogs Albrecht VI. von Bayern, der "Leuchtenberger" (1584-1666) (lang:de)                           |

Answer: There are 2,363 paintings in the Bavarian State Painting Collections with German labels ending in ")". Examples include "Martyrium der thebaischen Legion (Vorderseite: Hll. Anno und Gregor der Mohr) (lang:de)" and "Bildnis des Peter Philipp von Dernbach, Fürstbischof von Bamberg und Würzburg (1619-1683) (lang:de)".

There are 2,363 paintings in the Bavarian State Painting Collections with German labels ending in ")". Examples include "Martyrium der thebaischen Legion (Vorderseite: Hll. Anno und Gregor der Mohr) (lang:de)" and "Bildnis des Peter Philipp von Dernbach, Fürstbischof von Bamberg und Würzburg (1619-1683) (lang:de)".

SPARQL query over wikidata:
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?painting ?label WHERE {
  ?painting wdt:P31 wd:Q3305213 ; wdt:P195 wd:Q812285 .
  ?painting rdfs:label ?label .
  FILTER ( LANG( ?label ) = "de" ) .
  FILTER ( STRENDS( ?label , ")" ) )
}

Using entities:
- painting (wd:Q3305213), also known as painting (object), paintings: is instance of type of work of art / is subclass of two-dimensional visual artwork / is subclass of work of art / is subclass of Work of art / surface artistically covered with paint / visual artwork, surface artistically covered with paint / visual artwork, surface artistically covered with paint
- Bavarian State Painting Collections (wd:Q812285), also known as Bayerische Staatsgemäldesammlungen, BStGS, Centralgemäldegaleriedirektion: is instance of art gallery / is instance of art museum / is instance of Art museum / is instance of art collection / artworks held by the Free State of Bavaria for Alte Pinakothek, Aschaffenburg, Bamberg, Bayreuth, Schleissheim and others

Using properties:
- collection (wd:P195 as wdt), also known as archival holdings, archives, art collection, bibliographic collection, book collection, etc.: is subproperty of part of / art, museum, archival, or bibliographic collection of which the subject is part / art, museum, archival, or bibliographic collection of which the subject is part
- instance of (wd:P31 as wdt), also known as example of, has type, is a, is an, is of type, etc.: that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform) / type to which this subject corresponds/belongs. Different ... and the volcano is a type (instance) of volcanic landform

Execution result:
Got 2,363 rows and 2 columns, showing the first 5 and last 5 rows below:
| painting                                       | label                                                                                |
| ---------------------------------------------- | ----------------------------------------------------------------------------------------------------------------- |
| Martyrdom of the Theban Legion (wd:Q101150344) | Martyrium der thebaischen Legion / Tod des hl. Gereon (Vorderseite: Hll. Stephanus und Mauritius) (lang:de)       |
| Martyrdom of the Theban Legion (wd:Q101153651) | Martyrium der thebaischen Legion (Vorderseite: Hll. Anno und Gregor der Mohr) (lang:de)                           |
| wd:Q111797391                                  | Maiabend (Nach dem Gewitter) (lang:de)                                                                            |
| wd:Q111798649                                  | Carona (Tessin) (lang:de)                                                                                |
| Abstract Head (pink lips) (wd:Q111798743)      | Abstrakter Kopf (Rosa Lippen) (lang:de)                                                                           |
| ...                                            | ...                                                                                |
| wd:Q62993550                                   | Bildnis des Peter Philipp von Dernbach, Fürstbischof von Bamberg und Würzburg (1619-1683) (lang:de)               |
| wd:Q62994594                                   | Kardinal Benedetto Odescalchi (1611 - 1689) (lang:de)                                                             |
| wd:Q62994788                                   | Kinderbildnis des Alexander Sigismund von Pfalz-Neuburg (1663-1737) (lang:de)                                     |
| wd:Q62999399                                   | Friedrich I. der Siegreiche, Pfalzgraf bei Rhein, Herzog von Bayern, Kurfürst von der Pfalz (1425-1476) (lang:de) |
| wd:Q63106949                                   | Bildnis des Herzogs Albrecht VI. von Bayern, der "Leuchtenberger" (1584-1666) (lang:de)                           |

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

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.

Available knowledge graphs:
- wikidata at http://localhost:7001 with prefix index for entities and similarity index for properties, and notes:
  - P106 = occupation. Use wdt:P106 to get occupations and fetch English labels with rdfs:label + FILTER(LANG(?label)="en"). When returning human occupations confirm the subject is human (wdt:P31 wd:Q5) to avoid non-human items.
  - Population (P1082) and tabular (P4179): use wdt:P1082 for quick/direct values; for time-series/point-in-time use p:P1082 + ps:P1082 + pq:P585 and ORDER BY pq:P585 DESC. Inspect statement qualifiers (e.g., 'applies to part') and prov:wasDerivedFrom references (pr:P854 etc.) to detect city-proper vs metro/prefecture scopes before using values.
  - Common person properties: P31 (instance of human Q5), P106 (occupation), P569 (date of birth), P19 (place of birth), P27 (country of citizenship), P21 (sex/gender), P166 (award received). Use wdt: for direct values when possible.
  - P17 (country) can be incomplete/misleading for places (historical/overseas tags). To get modern cities in a country combine: instance-of city (P31=Q515) + wdt:P17 OR use wdt:P131* to find an admin parent whose wdt:P17 = the country. Also cross-check coordinates (P625) or admin hierarchy to spot outliers.
  - When filtering by date of birth (P569) use xsd:dateTime comparisons (e.g. >= "1900-01-01T00:00:00Z"^^xsd:dateTime). Be aware many items have year-only or imprecise dates and coverage is biased toward notable/public figures (sportspeople, politicians, artists).
  - To retrieve qualifiers (e.g., award year) use the statement/qualifier pattern: p:Pxxx / ps:Pxxx / pq:P585. Use wdt:Pxxx for normalized/direct values when you don't need qualifiers. Example: p:P166 + pq:P585 gives award year.
  - To get a person's occupations: use wdt:P106 for direct/normalized values and rdfs:label for human-readable names (FILTER(LANG(...))). Example: wd:Q... wdt:P106 ?occ . ?occ rdfs:label ?occLabel . FILTER(LANG(?occLabel)="en").
  - P166 = award received. Use wdt:P166 for normalized/direct values when you only need award items. To get award years or qualifiers use p:P166 / ps:P166 / pq:P585. Many statements lack pq:P585 — use OPTIONAL { ?stmt pq:P585 ?date } and ORDER BY DESC(?date). When listing award winners, filter ?person wdt:P31 wd:Q5 to ensure humans.
  - Population time-series pattern: wd:Q... p:P1082 ?stmt . ?stmt ps:P1082 ?pop . OPTIONAL { ?stmt pq:P585 ?date } . ORDER BY DESC(?date). pq:P585 is the point-in-time qualifier. IMPORTANT: time-series may mix scopes (city proper vs metro) — e.g., Tokyo has a 2016 entry ~38,140,000 likely metro vs smaller city figures. Inspect qualifiers/references for scope before use.
  - Use wdt:P131* to traverse the admin hierarchy and compare wdt:P17 on the place vs an admin parent to detect historical/colonial country assignments. When mismatches appear, inspect the admin parent's instance-of (P31), labels, qualifiers and references to interpret the historical scope.
  - wdt:P106 often yields multiple occupations for a person. Use GROUP_CONCAT(DISTINCT ?occLabel; separator=", ") or return multiple rows. Always fetch labels with rdfs:label + FILTER(LANG(?label)="en") to get readable occupation names.
  - When a search_entity returns multiple hits (person vs sculpture vs memorial), confirm you selected the human/statements by checking wdt:P31 (instance of) and relevant wdt: properties (e.g., wdt:P106). This avoids using a non-human QID by mistake.
  - search_autocomplete can be constrained with a SPARQL pattern containing ?search (e.g., SELECT * WHERE { ?search wdt:P31 wd:Q5 }). Use constraints to focus results (e.g., humans) and avoid ambiguous fallbacks; if it returns no results, fallback to search_entity and verify wdt:P31.
  - Use search_property_of_entity to find relevant properties for an entity (e.g., 'award' -> P166) and search_object_of_property to discover candidate objects (e.g., 'physicist' for P106). This reduces guessing P/Q ids and surfaces qualifiers.
  - Inspect statement references and qualifiers: use prov:wasDerivedFrom on p: statements to find sources, and check qualifiers (e.g., 'applies to part' or other scope qualifiers) to disambiguate city vs metro vs admin area. Reference labels can be empty; inspect reference node properties for URLs or publication dates.

Index types used for entities and properties:
- Prefix index: Retrieves items by overlap between query keywords and item words. The query keywords can match item words exactly or as prefixes.
- Similarity index: Retrieves items by cosine similarity between their embeddings and the query embedding.

General notes across knowledge graphs:
- Use rdfs:label + FILTER(LANG(?label)="en") for labels; avoid SERVICE wikibase:label. Use wdt:Pxxx for normalized/direct values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access statement qualifiers (e.g., award year via pq:P585). When dates matter, prefer xsd:dateTime and watch for year-only precision.
- Practical query patterns: use rdfs:label + FILTER(LANG(...)) for labels. Use wdt:Pxxx for direct/normalized values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access qualifiers (dates via pq:P585). For dates use xsd:dateTime and expect year-only precision. For places: combine P17 with P131 or coordinate (P625) filters to avoid historical/overseas mismatches.
- Use OPTIONAL for pq: qualifiers (e.g., pq:P585), sort by qualifier (ORDER BY pq:P585 DESC) to prefer recent values. Use GROUP_CONCAT to combine multiple labels/values in one row. Watch for typed literals (xsd:dateTime, xsd:decimal) when filtering or sorting.
- Before querying, use search_entity to resolve human-friendly names to wd:Q identifiers and verify instance-of (e.g., check wdt:P31 = wd:Q5 for humans) to avoid ambiguous matches. Prefer the top match but programmatically confirm P31 before using its data.
- Use search_property to confirm property identifiers (e.g., "country" -> P17) before embedding them in queries. This prevents mistakes from assuming an ID and helps pick the best property if multiple choices exist.
- search_autocomplete can fall back to an unconstrained search or error when there are too many candidates. If this happens (e.g., "more than the maximum supported number of subject candidates"), retry with narrower constraints such as instance-of (wdt:P31), additional type filters, or short prefixes to reduce the candidate set; otherwise fallback to search_entity and verify wdt:P31.
- Use list(...) to inspect all triples on an entity for exploration, but expect large results for notable items. Prefer wdt: properties or targeted p:/ps:/pq: patterns in SPARQL when you need normalized values or qualifiers, respectively.
- Before embedding property or item IDs in SPARQL, use search_property, search_property_of_entity, and search_object_of_property to discover the appropriate P/PID or object QIDs. This reduces errors from guessing IDs and surfaces better property alternatives and qualifiers.
- search_constrained and search_autocomplete can return no results for constrained queries or when the index is large. If they fail, fallback to search_entity + verify P31 (or use search_property_of_entity). Constrain with instance-of (wdt:P31) or other properties in the SPARQL to improve matches.
- When selecting awards by year, prefer xsd:dateTime range filters (e.g., >= "2001-01-01T00:00:00Z"^^xsd:dateTime && < "2002-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for portability and precision.
- When selecting award winners via wdt:P166, filter ?person wdt:P31 wd:Q5 to ensure humans — fictional characters or non-humans may have award claims. If you need award years use p:P166 / ps:P166 / pq:P585 and OPTIONAL { ?stmt pq:P585 ?year } to retrieve qualifier years.
- Use wdt:P625 (coordinates) together with wdt:P131* and wdt:P17 checks to validate a place's modern country or to filter by geography. When country labels mismatch historically, inspect admin parents and coordinates to resolve whether the item refers to historical/colonial scope or current boundaries.
- Prefer wdt:Pxxx for normalized/direct values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access qualifiers (e.g., pq:P585 for award year). Always fetch labels with rdfs:label + FILTER(LANG(?label) = "en").
- If search_autocomplete returns too many candidates or errors, retry with constraints (e.g., SELECT * WHERE { ?search wdt:P31 wd:Q5 }) or narrower query text. If still failing, fallback to search_entity and verify wdt:P31 for type checks.
- For award-year queries use p:P166 / ps:P166 / pq:P585 to access award statements and year qualifiers. Filter by xsd:dateTime ranges (e.g., >= "2020-01-01T00:00:00Z"^^xsd:dateTime && < "2021-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for robustness.
- Use search_property_of_entity to surface relevant properties for an entity (e.g., 'birth' -> P569/P19). list(...) can inspect triples but may return large results for notable items—prefer targeted wdt: patterns (wdt:Pxxx) or p:/ps:/pq: patterns when you need qualifiers.

SPARQL prefixes for use in function calls:
- bd: <http://www.bigdata.com/rdf#
- cc: <http://creativecommons.org/ns#
- data: <https://www.wikidata.org/wiki/Special:EntityData/
- dc: <http://purl.org/dc/elements/1.1/
- dct: <http://purl.org/dc/terms/
- foaf: <http://xmlns.com/foaf/0.1/
- geo: <http://www.opengis.net/ont/geosparql#
- geof: <http://www.opengis.net/def/function/geosparql/
- gn: <http://www.geonames.org/ontology#
- hint: <http://www.bigdata.com/queryHints#
- imdb: <https://www.imdb.com/
- math: <http://www.w3.org/2005/xpath-functions/math#
- ontolex: <http://www.w3.org/ns/lemon/ontolex#
- owl: <http://www.w3.org/2002/07/owl#
- p: <http://www.wikidata.org/prop/
- pq: <http://www.wikidata.org/prop/qualifier/
- pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
- pqv: <http://www.wikidata.org/prop/qualifier/value/
- pr: <http://www.wikidata.org/prop/reference/
- prn: <http://www.wikidata.org/prop/reference/value-normalized/
- prov: <http://www.w3.org/ns/prov#
- prv: <http://www.wikidata.org/prop/reference/value/
- ps: <http://www.wikidata.org/prop/statement/
- psn: <http://www.wikidata.org/prop/statement/value-normalized/
- psv: <http://www.wikidata.org/prop/statement/value/
- qb: <http://purl.org/linked-data/cube#
- qfn: <http://qlever.cs.uni-freiburg.de/function#
- ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
- qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
- rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
- rdfs: <http://www.w3.org/2000/01/rdf-schema#
- ref: <http://www.wikidata.org/reference/
- s: <http://www.wikidata.org/entity/statement/
- schema: <http://schema.org/
- skos: <http://www.w3.org/2004/02/skos/core#
- v: <http://www.wikidata.org/value/
- void: <http://rdfs.org/ns/void#
- wd: <http://www.wikidata.org/entity/
- wdno: <http://www.wikidata.org/prop/novalue/
- wdt: <http://www.wikidata.org/prop/direct/
- wdtn: <http://www.wikidata.org/prop/direct-normalized/
- wikibase: <http://wikiba.se/ontology#
- xsd: <http://www.w3.org/2001/XMLSchema#

Additional rules to follow:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- Do not ask the user for clarifications without first attempting to complete the task. If the task input is incomplete or ambiguous, try to make reasonable assumptions and document them.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] What are the paintings in the Bavarian State Painting Collections with labels in German that end in ")"?

[Assistant]
To answer the question about paintings in the Bavarian State Painting Collections with labels in German that end in ")", I need to:

1. Identify the relevant entity for the "Bavarian State Painting Collections" in Wikidata.
2. Find paintings that are part of this collection.
3. Filter for paintings that have a German label (rdfs:label) ending with ")".

### Step 1: Search for the entity "Bavarian State Painting Collections"
I'll start by searching for the entity corresponding to the Bavarian State Painting Collections.

Question: Bavarian State Painting Collections

Top 10 entity alternatives:
1. Bavarian State Painting Collections (wd:Q812285), also known as Bayerische Staatsgemäldesammlungen, BStGS, Centralgemäldegaleriedirektion: artworks held by the Free State of Bavaria for Alte Pinakothek, Aschaffenburg, Bamberg, Bayreuth, Schleissheim and others / is instance of art collection / is instance of art gallery / is instance of art museum / is instance of Art museum
2. Bavarian State Painting Collections Online Collection (wd:Q111321393), also known as Online Collection of the Bavarian State Painting Collections: is instance of online collection / is instance of online database
3. Five Paintings from the Bavarian State Paintings Collections (wd:Q115038818): 1976–1978 Exhibition at Metropolitan Museum / is instance of art exhibition
4. locations of the Bavarian State Painting Collections with works not on display (wd:Q29343881), also known as BStGS depot: is instance of museum storage
5. Bavarian State Library (wd:Q256507), also known as Bayerische Staatsbibliothek, Bibliotheca Regia Monacensis, BSB, bsb-muenchen.de: is instance of United Nations Depository Library / state library of the Free State of Bavaria / is instance of state library of Germany / is instance of universal library / is instance of reference library / is instance of research library / is instance of state library
6. Bavarian State Opera (wd:Q681931): opera company in Munich, Germany / is instance of opera company
7. Bavarian State Brewery Weihenstephan (wd:Q812294), also known as Weihenstephaner: is instance of Brewery / is instance of brewery / brewery
8. 2018 Bavarian state election (wd:Q19833920), also known as 2018 Bavaria state election: is instance of state election in Bavaria / state election in Bavaria, Germany
9. Bavarian State Orchestra (wd:Q683117), also known as Bavarian State Opera Orchestra: is instance of orchestra / orchestra
10. 2013 Bavarian state election (wd:Q1250713), also known as 2013 Bavaria state election: is instance of state election in Bavaria / state election in Bavaria, Germany

[Assistant]
The top result is `wd:Q812285` — "Bavarian State Painting Collections" — which is an art collection that holds artworks in various locations like Alte Pinakothek, etc. This is the correct entity to use.

### Step 2: Find paintings that are part of this collection
Paintings are typically instances of `wd:Q3305213` (painting) in Wikidata. We need to find paintings that are part of the collection `wd:Q812285`.

In Wikidata, the property for "collection" or "held by" is often `wdt:P195` (collection). So I will look for paintings with:
- `wdt:P31 wd:Q3305213` (instance of painting)
- `wdt:P195 wd:Q812285` (part of Bavarian State Painting Collections)

### Step 3: Get German labels ending in ")"
We need to get the German labels (`rdfs:label`) of these paintings and filter those ending in ")". We'll use `FILTER(LANG(?label) = "de")` and `FILTER(STRENDS(?label, ")"))`.

### Step 4: Construct the SPARQL query
Now I'll construct the SPARQL query to:
- Select paintings that are in the Bavarian State Painting Collections
- Filter for German labels ending in ")"
- Return the label

Let me execute this query.

execute

SELECT ?painting ?label WHERE { ?painting wdt:P31 wd:Q3305213 ; wdt:P195 wd:Q812285 . ?painting rdfs:label ?label . FILTER(LANG(?label) = "de") . FILTER(STRENDS(?label, ")")) }

Got 2,363 rows and 2 columns, showing the first 5 and last 5 rows below:
| painting                                       | label                                                                                |
| ---------------------------------------------- | ----------------------------------------------------------------------------------------------------------------- |
| Martyrdom of the Theban Legion (wd:Q101150344) | Martyrium der thebaischen Legion / Tod des hl. Gereon (Vorderseite: Hll. Stephanus und Mauritius) (lang:de)       |
| Martyrdom of the Theban Legion (wd:Q101153651) | Martyrium der thebaischen Legion (Vorderseite: Hll. Anno und Gregor der Mohr) (lang:de)                           |
| wd:Q111797391                                  | Maiabend (Nach dem Gewitter) (lang:de)                                                                            |
| wd:Q111798649                                  | Carona (Tessin) (lang:de)                                                                                |
| Abstract Head (pink lips) (wd:Q111798743)      | Abstrakter Kopf (Rosa Lippen) (lang:de)                                                                           |
| ...                                            | ...                                                                                |
| wd:Q62993550                                   | Bildnis des Peter Philipp von Dernbach, Fürstbischof von Bamberg und Würzburg (1619-1683) (lang:de)               |
| wd:Q62994594                                   | Kardinal Benedetto Odescalchi (1611 - 1689) (lang:de)                                                             |
| wd:Q62994788                                   | Kinderbildnis des Alexander Sigismund von Pfalz-Neuburg (1663-1737) (lang:de)                                     |
| wd:Q62999399                                   | Friedrich I. der Siegreiche, Pfalzgraf bei Rhein, Herzog von Bayern, Kurfürst von der Pfalz (1425-1476) (lang:de) |
| wd:Q63106949                                   | Bildnis des Herzogs Albrecht VI. von Bayern, der "Leuchtenberger" (1584-1666) (lang:de)                           |

[Assistant]
The query successfully returned 2,363 paintings from the Bavarian State Painting Collections with German labels ending in ")". The results show that the labels are indeed in German and end with ")", as required. Examples include:

- "Martyrium der thebaischen Legion (Vorderseite: Hll. Anno und Gregor der Mohr) (lang:de)"
- "Bildnis des Peter Philipp von Dernbach, Fürstbischof von Bamberg und Würzburg (1619-1683) (lang:de)"

The query is correct and returns exactly what was asked: paintings in the Bavarian State Painting Collections with German labels ending in ")".

I will now provide the final answer with the SPARQL query.

answer

SELECT ?painting ?label WHERE { ?painting wdt:P31 wd:Q3305213 ; wdt:P195 wd:Q812285 . ?painting rdfs:label ?label . FILTER(LANG(?label) = "de") . FILTER(STRENDS(?label, ")")) }

Answer: There are 2,363 paintings in the Bavarian State Painting Collections with German labels ending in ")". Examples include "Martyrium der thebaischen Legion (Vorderseite: Hll. Anno und Gregor der Mohr) (lang:de)" and "Bildnis des Peter Philipp von Dernbach, Fürstbischof von Bamberg und Würzburg (1619-1683) (lang:de)".


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE {
  ?person wdt:P31 wd:Q5 ; wdt:P106 ?occupation ; wdt:P27 wd:Q30 ; wdt:P19 wd:Q771 ; wdt:P569 ?dateOfBirth .
  FILTER ( ?dateOfBirth >= "1919-12-31T00:00:00Z" ^^ xsd:dateTime ) OPTIONAL {
    ?person wdt:P570 ?deathDate
  }
  FILTER ( ! BOUND( ?deathDate ) ) ?person wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel .
  FILTER ( LANG( ?birthPlaceLabel ) = "en" ) FILTER ( ?occupation IN ( wd:Q482980 , wd:Q36180 ) )
}
ORDER BY ?dateOfBirth

Using entities:
- United States (wd:Q30), also known as America, Merica, Murica, the States, the United States, etc.: is instance of superpower / is instance of sovereign state / is instance of federal republic / is instance of Federal republic / is instance of constitutional republic / is instance of democratic republic / is instance of country / country in North America / country in North America / country primarily located in North America
- writer (wd:Q36180), also known as author, authors, penman, penmen, penwoman, etc.: is instance of occupation / is instance of profession / is subclass of penman / is subclass of author / is subclass of artist / person who uses written words to communicate ideas and to produce literary works / person who uses written words to communicate ideas and to produce works of literature / person who uses written words to communicate ideas, person who produces written works
- author (wd:Q482980), also known as authors, contributor, contributors: is instance of occupation / is subclass of creator / a writer of a book, article, or document / writer of an original work
- human (wd:Q5), also known as human being, humans, individual Homo sapiens, individual human, modern humans, etc.: is instance of class of organisms known by one particular common name / is instance of organisms known by a particular common name / is subclass of mammal / is subclass of natural person / is subclass of omnivore / is subclass of person / is subclass of individual animal / any member of Homo sapiens, unique extant species of the genus Homo / common name of Homo sapiens, unique extant species of the genus Homo / common name of Homo sapiens, unique extant species of the genus Homo / common name of Homo sapiens, unique extant species of the genus Homo, from embryo to adult
- Massachusetts (wd:Q771), also known as 6th State, Bay State, Commonwealth of MA, Commonwealth of Massachusetts, MA, etc.: is instance of U.S. state / is instance of state of the United States / state of the United States of America / state of the United States of America / state of the United States of America

Using properties:
- occupation (wd:P106 as wdt), also known as avocation, career, craft, employ, employment, etc.: occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39) / occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39) / occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
- place of birth (wd:P19 as wdt), also known as birth city, birth location, birth place, birthplace, born, etc.: is subproperty of location / most specific known birth location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... birth location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... birth location of a person, animal or fictional character
- country of citizenship (wd:P27 as wdt), also known as citizen of, citizenship, country, (legal) nationality, nation, etc.: is subproperty of country / the object is a country that recognizes the subject as its citizen / the object is a country that recognizes the subject as its citizen
- instance of (wd:P31 as wdt), also known as example of, has type, is a, is an, is of type, etc.: that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform) / type to which this subject corresponds/belongs. Different ... and the volcano is a type (instance) of volcanic landform
- date of birth (wd:P569 as wdt), also known as birth date, birthdate, birth year, birthyear, born, etc.: is subproperty of inception / is subproperty of date of foundation or creation / date on which the subject was born / date on which the subject was born / date on which the subject was born
- date of death (wd:P570 as wdt), also known as date of the end, dead, death, death date, deathdate, etc.: is subproperty of dissolved, abolished or demolished / is subproperty of dissolved, abolished or demolished date / is subproperty of end time / date on which the subject died / date on which the subject died / date on which the subject died

Got 25 rows and 3 columns, showing the first 5 and last 5 rows below:
| person                              | dateOfBirth                         | birthPlaceLabel         |
| ----------------------------------- | ----------------------------------- | ----------------------- |
| Joan Larkin (wd:Q13563279)          | 1939-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Sara Pennypacker (wd:Q7421740)      | 1951-12-09T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Dara Joy (wd:Q20497946)             | 1952-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Michael Tonello (wd:Q6834918)       | 1958-07-19T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Suzanne Strempek Shea (wd:Q7650975) | 1958-12-07T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| ...                                 | ...                                 | ...                     |
| Sarah Manguso (wd:Q2224436)         | 1974-02-12T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Jason M. Burns (wd:Q6163000)        | 1978-03-17T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Sarah Jaffe (wd:Q55617913)          | 1980-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Haroon Moghul (wd:Q16203638)        | 1980-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Wu Tsang (wd:Q17581477)             | 1982-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |

Answer:
The query successfully returned 25 living authors who are U.S. citizens, born in Massachusetts after 1919, with their birthplace and date of birth, ordered by date of birth. The results include notable authors such as Joan Larkin (born 1939), Sara Pennypacker (born 1951), and Wu Tsang (born 1982), all with birthplace labeled as "Massachusetts" in English.

### Final Answer:
The SPARQL query correctly retrieves the requested information. Here is the final answer:

```sparql
SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE {
  ?person wdt:P31 wd:Q5 ;                    # is a human
          wdt:P106 ?occupation ;
          wdt:P27 wd:Q30 ;                   # citizenship: United States
          wdt:P19 wd:Q771 ;                  # birthplace: Massachusetts
          wdt:P569 ?dateOfBirth .            # date of birth
  FILTER(?dateOfBirth >= "1919-12-31T00:00:00Z"^^xsd:dateTime)  # born after 1919
  OPTIONAL { ?person wdt:P570 ?deathDate }   # check for death date
  FILTER(!BOUND(?deathDate))                 # ensure person is alive
  ?person wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel .
  FILTER(LANG(?birthPlaceLabel) = "en")
  FILTER(?occupation IN (wd:Q482980, wd:Q36180))
} ORDER BY ?dateOfBirth
```

The results show 25 living authors meeting the criteria, with birthplace as "Massachusetts" and dates of birth from 1939 to 1982.

answer(kg="wikidata", sparql="SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE { ?person wdt:P31 wd:Q5 ; wdt:P106 ?occupation ; wdt:P27 wd:Q30 ; wdt:P19 wd:Q771 ; wdt:P569 ?dateOfBirth . FILTER(?dateOfBirth >= \"1919-12-31T00:00:00Z\"^^xsd:dateTime) OPTIONAL { ?person wdt:P570 ?deathDate } FILTER(!BOUND(?deathDate)) ?person wdt:P19 ?birthPlace . ?birthPlace rdfs:label ?birthPlaceLabel . FILTER(LANG(?birthPlaceLabel) = \"en\") FILTER(?occupation IN (wd:Q482980, wd:Q36180)) } ORDER BY ?dateOfBirth", answer="There are 25 living authors who are citizens of the United States, were born in Massachusetts after 1919. Their birthplace is Massachusetts, and their dates of birth range from 1939 to 1982. Examples include Joan Larkin (born 1939), Sara Pennypacker (born 1951), and Wu Tsang (born 1982).")

The query successfully returned 25 living authors who are U.S. citizens, born in Massachusetts after 1919, with their birthplace and date of birth, ordered by date of birth. The results include notable authors such as Joan Larkin (born 1939), Sara Pennypacker (born 1951), and Wu Tsang (born 1982), all with birthplace labeled as "Massachusetts" in English.

### Final Answer:
The SPARQL query correctly retrieves the requested information. Here is the final answer:

```sparql
SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE {
  ?person wdt:P31 wd:Q5 ;                    # is a human
          wdt:P106 ?occupation ;
          wdt:P27 wd:Q30 ;                   # citizenship: United States
          wdt:P19 wd:Q771 ;                  # birthplace: Massachusetts
          wdt:P569 ?dateOfBirth .            # date of birth
  FILTER(?dateOfBirth >= "1919-12-31T00:00:00Z"^^xsd:dateTime)  # born after 1919
  OPTIONAL { ?person wdt:P570 ?deathDate }   # check for death date
  FILTER(!BOUND(?deathDate))                 # ensure person is alive
  ?person wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel .
  FILTER(LANG(?birthPlaceLabel) = "en")
  FILTER(?occupation IN (wd:Q482980, wd:Q36180))
} ORDER BY ?dateOfBirth
```

The results show 25 living authors meeting the criteria, with birthplace as "Massachusetts" and dates of birth from 1939 to 1982.

answer(kg="wikidata", sparql="SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE { ?person wdt:P31 wd:Q5 ; wdt:P106 ?occupation ; wdt:P27 wd:Q30 ; wdt:P19 wd:Q771 ; wdt:P569 ?dateOfBirth . FILTER(?dateOfBirth >= \"1919-12-31T00:00:00Z\"^^xsd:dateTime) OPTIONAL { ?person wdt:P570 ?deathDate } FILTER(!BOUND(?deathDate)) ?person wdt:P19 ?birthPlace . ?birthPlace rdfs:label ?birthPlaceLabel . FILTER(LANG(?birthPlaceLabel) = \"en\") FILTER(?occupation IN (wd:Q482980, wd:Q36180)) } ORDER BY ?dateOfBirth", answer="There are 25 living authors who are citizens of the United States, were born in Massachusetts after 1919. Their birthplace is Massachusetts, and their dates of birth range from 1939 to 1982. Examples include Joan Larkin (born 1939), Sara Pennypacker (born 1951), and Wu Tsang (born 1982).")

SPARQL query over wikidata:
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE {
  ?person wdt:P31 wd:Q5 ; wdt:P106 ?occupation ; wdt:P27 wd:Q30 ; wdt:P19 wd:Q771 ; wdt:P569 ?dateOfBirth .
  FILTER ( ?dateOfBirth >= "1919-12-31T00:00:00Z" ^^ xsd:dateTime ) OPTIONAL {
    ?person wdt:P570 ?deathDate
  }
  FILTER ( ! BOUND( ?deathDate ) ) ?person wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel .
  FILTER ( LANG( ?birthPlaceLabel ) = "en" ) FILTER ( ?occupation IN ( wd:Q482980 , wd:Q36180 ) )
}
ORDER BY ?dateOfBirth

Using entities:
- United States (wd:Q30), also known as America, Merica, Murica, the States, the United States, etc.: is instance of superpower / is instance of sovereign state / is instance of federal republic / is instance of Federal republic / is instance of constitutional republic / is instance of democratic republic / is instance of country / country in North America / country in North America / country primarily located in North America
- writer (wd:Q36180), also known as author, authors, penman, penmen, penwoman, etc.: is instance of occupation / is instance of profession / is subclass of penman / is subclass of author / is subclass of artist / person who uses written words to communicate ideas and to produce literary works / person who uses written words to communicate ideas and to produce works of literature / person who uses written words to communicate ideas, person who produces written works
- author (wd:Q482980), also known as authors, contributor, contributors: is instance of occupation / is subclass of creator / a writer of a book, article, or document / writer of an original work
- human (wd:Q5), also known as human being, humans, individual Homo sapiens, individual human, modern humans, etc.: is instance of class of organisms known by one particular common name / is instance of organisms known by a particular common name / is subclass of mammal / is subclass of natural person / is subclass of omnivore / is subclass of person / is subclass of individual animal / any member of Homo sapiens, unique extant species of the genus Homo / common name of Homo sapiens, unique extant species of the genus Homo / common name of Homo sapiens, unique extant species of the genus Homo / common name of Homo sapiens, unique extant species of the genus Homo, from embryo to adult
- Massachusetts (wd:Q771), also known as 6th State, Bay State, Commonwealth of MA, Commonwealth of Massachusetts, MA, etc.: is instance of U.S. state / is instance of state of the United States / state of the United States of America / state of the United States of America / state of the United States of America

Using properties:
- occupation (wd:P106 as wdt), also known as avocation, career, craft, employ, employment, etc.: occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39) / occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39) / occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
- place of birth (wd:P19 as wdt), also known as birth city, birth location, birth place, birthplace, born, etc.: is subproperty of location / most specific known birth location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... birth location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... birth location of a person, animal or fictional character
- country of citizenship (wd:P27 as wdt), also known as citizen of, citizenship, country, (legal) nationality, nation, etc.: is subproperty of country / the object is a country that recognizes the subject as its citizen / the object is a country that recognizes the subject as its citizen
- instance of (wd:P31 as wdt), also known as example of, has type, is a, is an, is of type, etc.: that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform) / type to which this subject corresponds/belongs. Different ... and the volcano is a type (instance) of volcanic landform
- date of birth (wd:P569 as wdt), also known as birth date, birthdate, birth year, birthyear, born, etc.: is subproperty of inception / is subproperty of date of foundation or creation / date on which the subject was born / date on which the subject was born / date on which the subject was born
- date of death (wd:P570 as wdt), also known as date of the end, dead, death, death date, deathdate, etc.: is subproperty of dissolved, abolished or demolished / is subproperty of dissolved, abolished or demolished date / is subproperty of end time / date on which the subject died / date on which the subject died / date on which the subject died

Execution result:
Got 25 rows and 3 columns, showing the first 5 and last 5 rows below:
| person                              | dateOfBirth                         | birthPlaceLabel         |
| ----------------------------------- | ----------------------------------- | ----------------------- |
| Joan Larkin (wd:Q13563279)          | 1939-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Sara Pennypacker (wd:Q7421740)      | 1951-12-09T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Dara Joy (wd:Q20497946)             | 1952-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Michael Tonello (wd:Q6834918)       | 1958-07-19T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Suzanne Strempek Shea (wd:Q7650975) | 1958-12-07T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| ...                                 | ...                                 | ...                     |
| Sarah Manguso (wd:Q2224436)         | 1974-02-12T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Jason M. Burns (wd:Q6163000)        | 1978-03-17T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Sarah Jaffe (wd:Q55617913)          | 1980-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Haroon Moghul (wd:Q16203638)        | 1980-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Wu Tsang (wd:Q17581477)             | 1982-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |

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

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.

Available knowledge graphs:
- wikidata at http://localhost:7001 with prefix index for entities and similarity index for properties, and notes:
  - P106 = occupation. Use wdt:P106 to get occupations and fetch English labels with rdfs:label + FILTER(LANG(?label)="en"). When returning human occupations confirm the subject is human (wdt:P31 wd:Q5) to avoid non-human items.
  - Population (P1082) and tabular (P4179): use wdt:P1082 for quick/direct values; for time-series/point-in-time use p:P1082 + ps:P1082 + pq:P585 and ORDER BY pq:P585 DESC. Inspect statement qualifiers (e.g., 'applies to part') and prov:wasDerivedFrom references (pr:P854 etc.) to detect city-proper vs metro/prefecture scopes before using values.
  - Common person properties: P31 (instance of human Q5), P106 (occupation), P569 (date of birth), P19 (place of birth), P27 (country of citizenship), P21 (sex/gender), P166 (award received). Use wdt: for direct values when possible.
  - P17 (country) can be incomplete/misleading for places (historical/overseas tags). To get modern cities in a country combine: instance-of city (P31=Q515) + wdt:P17 OR use wdt:P131* to find an admin parent whose wdt:P17 = the country. Also cross-check coordinates (P625) or admin hierarchy to spot outliers.
  - When filtering by date of birth (P569) use xsd:dateTime comparisons (e.g. >= "1900-01-01T00:00:00Z"^^xsd:dateTime). Be aware many items have year-only or imprecise dates and coverage is biased toward notable/public figures (sportspeople, politicians, artists).
  - To retrieve qualifiers (e.g., award year) use the statement/qualifier pattern: p:Pxxx / ps:Pxxx / pq:P585. Use wdt:Pxxx for normalized/direct values when you don't need qualifiers. Example: p:P166 + pq:P585 gives award year.
  - To get a person's occupations: use wdt:P106 for direct/normalized values and rdfs:label for human-readable names (FILTER(LANG(...))). Example: wd:Q... wdt:P106 ?occ . ?occ rdfs:label ?occLabel . FILTER(LANG(?occLabel)="en").
  - P166 = award received. Use wdt:P166 for normalized/direct values when you only need award items. To get award years or qualifiers use p:P166 / ps:P166 / pq:P585. Many statements lack pq:P585 — use OPTIONAL { ?stmt pq:P585 ?date } and ORDER BY DESC(?date). When listing award winners, filter ?person wdt:P31 wd:Q5 to ensure humans.
  - Population time-series pattern: wd:Q... p:P1082 ?stmt . ?stmt ps:P1082 ?pop . OPTIONAL { ?stmt pq:P585 ?date } . ORDER BY DESC(?date). pq:P585 is the point-in-time qualifier. IMPORTANT: time-series may mix scopes (city proper vs metro) — e.g., Tokyo has a 2016 entry ~38,140,000 likely metro vs smaller city figures. Inspect qualifiers/references for scope before use.
  - Use wdt:P131* to traverse the admin hierarchy and compare wdt:P17 on the place vs an admin parent to detect historical/colonial country assignments. When mismatches appear, inspect the admin parent's instance-of (P31), labels, qualifiers and references to interpret the historical scope.
  - wdt:P106 often yields multiple occupations for a person. Use GROUP_CONCAT(DISTINCT ?occLabel; separator=", ") or return multiple rows. Always fetch labels with rdfs:label + FILTER(LANG(?label)="en") to get readable occupation names.
  - When a search_entity returns multiple hits (person vs sculpture vs memorial), confirm you selected the human/statements by checking wdt:P31 (instance of) and relevant wdt: properties (e.g., wdt:P106). This avoids using a non-human QID by mistake.
  - search_autocomplete can be constrained with a SPARQL pattern containing ?search (e.g., SELECT * WHERE { ?search wdt:P31 wd:Q5 }). Use constraints to focus results (e.g., humans) and avoid ambiguous fallbacks; if it returns no results, fallback to search_entity and verify wdt:P31.
  - Use search_property_of_entity to find relevant properties for an entity (e.g., 'award' -> P166) and search_object_of_property to discover candidate objects (e.g., 'physicist' for P106). This reduces guessing P/Q ids and surfaces qualifiers.
  - Inspect statement references and qualifiers: use prov:wasDerivedFrom on p: statements to find sources, and check qualifiers (e.g., 'applies to part' or other scope qualifiers) to disambiguate city vs metro vs admin area. Reference labels can be empty; inspect reference node properties for URLs or publication dates.

Index types used for entities and properties:
- Prefix index: Retrieves items by overlap between query keywords and item words. The query keywords can match item words exactly or as prefixes.
- Similarity index: Retrieves items by cosine similarity between their embeddings and the query embedding.

General notes across knowledge graphs:
- Use rdfs:label + FILTER(LANG(?label)="en") for labels; avoid SERVICE wikibase:label. Use wdt:Pxxx for normalized/direct values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access statement qualifiers (e.g., award year via pq:P585). When dates matter, prefer xsd:dateTime and watch for year-only precision.
- Practical query patterns: use rdfs:label + FILTER(LANG(...)) for labels. Use wdt:Pxxx for direct/normalized values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access qualifiers (dates via pq:P585). For dates use xsd:dateTime and expect year-only precision. For places: combine P17 with P131 or coordinate (P625) filters to avoid historical/overseas mismatches.
- Use OPTIONAL for pq: qualifiers (e.g., pq:P585), sort by qualifier (ORDER BY pq:P585 DESC) to prefer recent values. Use GROUP_CONCAT to combine multiple labels/values in one row. Watch for typed literals (xsd:dateTime, xsd:decimal) when filtering or sorting.
- Before querying, use search_entity to resolve human-friendly names to wd:Q identifiers and verify instance-of (e.g., check wdt:P31 = wd:Q5 for humans) to avoid ambiguous matches. Prefer the top match but programmatically confirm P31 before using its data.
- Use search_property to confirm property identifiers (e.g., "country" -> P17) before embedding them in queries. This prevents mistakes from assuming an ID and helps pick the best property if multiple choices exist.
- search_autocomplete can fall back to an unconstrained search or error when there are too many candidates. If this happens (e.g., "more than the maximum supported number of subject candidates"), retry with narrower constraints such as instance-of (wdt:P31), additional type filters, or short prefixes to reduce the candidate set; otherwise fallback to search_entity and verify wdt:P31.
- Use list(...) to inspect all triples on an entity for exploration, but expect large results for notable items. Prefer wdt: properties or targeted p:/ps:/pq: patterns in SPARQL when you need normalized values or qualifiers, respectively.
- Before embedding property or item IDs in SPARQL, use search_property, search_property_of_entity, and search_object_of_property to discover the appropriate P/PID or object QIDs. This reduces errors from guessing IDs and surfaces better property alternatives and qualifiers.
- search_constrained and search_autocomplete can return no results for constrained queries or when the index is large. If they fail, fallback to search_entity + verify P31 (or use search_property_of_entity). Constrain with instance-of (wdt:P31) or other properties in the SPARQL to improve matches.
- When selecting awards by year, prefer xsd:dateTime range filters (e.g., >= "2001-01-01T00:00:00Z"^^xsd:dateTime && < "2002-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for portability and precision.
- When selecting award winners via wdt:P166, filter ?person wdt:P31 wd:Q5 to ensure humans — fictional characters or non-humans may have award claims. If you need award years use p:P166 / ps:P166 / pq:P585 and OPTIONAL { ?stmt pq:P585 ?year } to retrieve qualifier years.
- Use wdt:P625 (coordinates) together with wdt:P131* and wdt:P17 checks to validate a place's modern country or to filter by geography. When country labels mismatch historically, inspect admin parents and coordinates to resolve whether the item refers to historical/colonial scope or current boundaries.
- Prefer wdt:Pxxx for normalized/direct values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access qualifiers (e.g., pq:P585 for award year). Always fetch labels with rdfs:label + FILTER(LANG(?label) = "en").
- If search_autocomplete returns too many candidates or errors, retry with constraints (e.g., SELECT * WHERE { ?search wdt:P31 wd:Q5 }) or narrower query text. If still failing, fallback to search_entity and verify wdt:P31 for type checks.
- For award-year queries use p:P166 / ps:P166 / pq:P585 to access award statements and year qualifiers. Filter by xsd:dateTime ranges (e.g., >= "2020-01-01T00:00:00Z"^^xsd:dateTime && < "2021-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for robustness.
- Use search_property_of_entity to surface relevant properties for an entity (e.g., 'birth' -> P569/P19). list(...) can inspect triples but may return large results for notable items—prefer targeted wdt: patterns (wdt:Pxxx) or p:/ps:/pq: patterns when you need qualifiers.

SPARQL prefixes for use in function calls:
- bd: <http://www.bigdata.com/rdf#
- cc: <http://creativecommons.org/ns#
- data: <https://www.wikidata.org/wiki/Special:EntityData/
- dc: <http://purl.org/dc/elements/1.1/
- dct: <http://purl.org/dc/terms/
- foaf: <http://xmlns.com/foaf/0.1/
- geo: <http://www.opengis.net/ont/geosparql#
- geof: <http://www.opengis.net/def/function/geosparql/
- gn: <http://www.geonames.org/ontology#
- hint: <http://www.bigdata.com/queryHints#
- imdb: <https://www.imdb.com/
- math: <http://www.w3.org/2005/xpath-functions/math#
- ontolex: <http://www.w3.org/ns/lemon/ontolex#
- owl: <http://www.w3.org/2002/07/owl#
- p: <http://www.wikidata.org/prop/
- pq: <http://www.wikidata.org/prop/qualifier/
- pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
- pqv: <http://www.wikidata.org/prop/qualifier/value/
- pr: <http://www.wikidata.org/prop/reference/
- prn: <http://www.wikidata.org/prop/reference/value-normalized/
- prov: <http://www.w3.org/ns/prov#
- prv: <http://www.wikidata.org/prop/reference/value/
- ps: <http://www.wikidata.org/prop/statement/
- psn: <http://www.wikidata.org/prop/statement/value-normalized/
- psv: <http://www.wikidata.org/prop/statement/value/
- qb: <http://purl.org/linked-data/cube#
- qfn: <http://qlever.cs.uni-freiburg.de/function#
- ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
- qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
- rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
- rdfs: <http://www.w3.org/2000/01/rdf-schema#
- ref: <http://www.wikidata.org/reference/
- s: <http://www.wikidata.org/entity/statement/
- schema: <http://schema.org/
- skos: <http://www.w3.org/2004/02/skos/core#
- v: <http://www.wikidata.org/value/
- void: <http://rdfs.org/ns/void#
- wd: <http://www.wikidata.org/entity/
- wdno: <http://www.wikidata.org/prop/novalue/
- wdt: <http://www.wikidata.org/prop/direct/
- wdtn: <http://www.wikidata.org/prop/direct-normalized/
- wikibase: <http://wikiba.se/ontology#
- xsd: <http://www.w3.org/2001/XMLSchema#

Additional rules to follow:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- Do not ask the user for clarifications without first attempting to complete the task. If the task input is incomplete or ambiguous, try to make reasonable assumptions and document them.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] What are the details of living authors who are citizens of the United States, were born in Massachusetts after 1919, including their birthplace and date of birth, ordered by their date of birth?

[Assistant]
To answer the question, we need to find living authors who are citizens of the United States, were born in Massachusetts after 1919, and retrieve their birthplace and date of birth, ordered by date of birth.

### Step 1: Identify relevant entities and properties
- **Occupation (P106)**: We need to find people whose occupation is "author". We can use `wdt:P106` to get the occupation and filter for "author".
- **Country of citizenship (P27)**: We need to filter for United States (Q30).
- **Place of birth (P19)**: We need to find people born in Massachusetts. Massachusetts is a U.S. state, so we need to identify its Wikidata ID (Q1321).
- **Date of birth (P569)**: We need to filter for people born after 1919. We will use `xsd:dateTime` comparisons.
- **Living**: To ensure the person is alive, we can check that they do not have a death date (`P570`). If `P570` is not present, we assume the person is alive.
- **Order by date of birth**: We will use `ORDER BY ?dateOfBirth`.

### Step 2: Search for the entity for "Massachusetts"
We need to confirm the Wikidata ID for Massachusetts. Let's search for it.

Question: Massachusetts

Top 10 entity alternatives:
1. Massachusetts (wd:Q771), also known as 6th State, Bay State, Commonwealth of MA, Commonwealth of Massachusetts, MA, etc.: is instance of state of the United States / state of the United States of America / state of the United States of America / state of the United States of America / is instance of U.S. state
2. 4547 Massachusetts (wd:Q1045311, matched via Massachusetts), also known as Massachusetts: is instance of asteroid / asteroid / asteroid / asteroid
3. Massachusetts (wd:Q656437), also known as Lights went out in Massachusetts, Massachusetts (The Lights Went Out In): is instance of musical work/composition / 1967 single by Bee Gees
4. Massachusetts (wd:Q6784161): original song written and composed by Arlo Guthrie / is instance of musical work/composition
5. Massachusetts (wd:Q1166387): 1973 double compilation album by Bee Gees / is instance of album
6. Massachusetts (wd:Q1166389): 1968 compilation album by Bee Gees / is instance of album
7. Massachusetts (wd:Q1166390): 1973 UK compilation album by The Bee Gees / is instance of album
8. How Can You Mend a Broken Heart / (The Lights Went Out In) Massachusetts (wd:Q1056006, matched via Massachusetts), also known as How Can You Mend a Broken Heart, Massachusetts, OS 13080, (The Lights Went Out In) Massachusetts: 1973 single by Bee Gees / is instance of single
9. Massachusetts (wd:Q3850885): 2013 single by Silverstein / is instance of single
10. Massachusetts (wd:Q17040616): 2013 studio album by Lori McKenna / is instance of album

[Assistant]
The correct entity for the U.S. state of Massachusetts is `wd:Q771`. We will use this in our query.

### Step 3: Search for the property for "author"
We need to confirm the property for "author" and ensure it is correctly mapped to `wdt:P106`. Let's search for objects of `wdt:P106` (occupation) with the query "author".

Question: author

Top 10 entity alternatives:
1. writer (wd:Q36180, matched via author), also known as author, authors, penman, penmen, penwoman, etc.: person who uses written words to communicate ideas and to produce works of literature / person who uses written words to communicate ideas, person who produces written works / person who uses written words to communicate ideas and to produce literary works / is instance of profession / is instance of occupation / is subclass of artist / is subclass of author / is subclass of penman
2. author (wd:Q482980), also known as authors, contributor, contributors: a writer of a book, article, or document / writer of an original work / is instance of occupation / is subclass of creator
3. MSC Corsica (wd:Q52322728, matched via Author), also known as Author, Benarmin, IMO 7905924, Safmarine Infanta, SCL Infanta: is instance of Container ship / is instance of container ship / scrapped container ship
4. poet (wd:Q49757, matched via poetry author), also known as bard, poetess, poetry author, poetry writer: is instance of profession / person who writes poetry / person who writes poetry / person who writes poetry / person who writes poetry / is subclass of writer
5. authority (wd:Q174834), also known as authority figure: legitimate power to decide or authorize / is instance of concept / is subclass of role
6. webmaster (wd:Q41674, matched via site author), also known as site author, web architect, web developer, webmistress, webops, etc.: person responsible for maintaining one or many websites / is subclass of software engineer / is instance of profession / is instance of position
7. authority (wd:Q4825937), also known as administration, management, rulership: asymmetric, hierarchical social relationship / is instance of type of power / is instance of social status / is instance of position / is instance of relation / is subclass of power
8. novelist (wd:Q6625963, matched via novel author), also known as novel author, novel writer: is instance of profession / is subclass of writer / writer of novels
9. anonymous (wd:Q4233718, matched via anonymous author), also known as Anon, anoniem, Anoniem, Anonymous, anonymous artist, etc.: unknown creator of a work (do not use as value of P50; use "unknown value" instead) / is subclass of unknown / has occupation artist / is instance of person
10. rapper (wd:Q2252262, matched via rap author), also known as rap artist, rap author, rap musician, rap performer, rappers, etc.: artist who speaks rhymes in a rhythm over music / artist who speaks rhymes in a rhythm over music / artist who speaks rhymes in a rhythm over music / artist who speaks rhymes in a rhythm over music / is instance of musical profession / is subclass of hip-hop musician / is instance of occupation / is subclass of vocalist

No other items found

No literal items found

[Assistant]
The most relevant entity for "author" is `wd:Q482980` (author). However, we also see `wd:Q36180` (writer) as a closely related occupation. Since the question asks for "authors," we will use `wd:Q482980` as the primary occupation, but we should also consider `wd:Q36180` (writer) as a broader category that may include authors. To be comprehensive, we will include both.

### Step 4: Confirm the country of citizenship for the United States
The United States is `wd:Q30`. We will use this directly.

### Step 5: Construct the SPARQL query
We need to:
1. Find people (`wdt:P31 wd:Q5` for humans).
2. Filter for occupation as "author" (`wdt:P106 wd:Q482980`) or "writer" (`wdt:P106 wd:Q36180`).
3. Filter for citizenship in the United States (`wdt:P27 wd:Q30`).
4. Filter for birthplace in Massachusetts (`wdt:P19 wd:Q771`).
5. Filter for date of birth after 1919 (`wdt:P569 >= "1919-12-31T00:00:00Z"^^xsd:dateTime`).
6. Ensure the person is alive (no death date, i.e., no `wdt:P570`).
7. Order by date of birth (`ORDER BY ?dateOfBirth`).

We will use `wdt:P569` for date of birth and `wdt:P19` for birthplace.

### Step 6: Write the SPARQL query
Here is the SPARQL query:

```sparql
SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE {
  ?person wdt:P31 wd:Q5 ;                    # is a human
          wdt:P106 wd:Q482980 ;              # occupation: author
          wdt:P27 wd:Q30 ;                   # citizenship: United States
          wdt:P19 wd:Q771 ;                  # birthplace: Massachusetts
          wdt:P569 ?dateOfBirth .            # date of birth
  FILTER(?dateOfBirth >= "1919-12-31T00:00:00Z"^^xsd:dateTime)  # born after 1919
  OPTIONAL { ?person wdt:P570 ?deathDate }   # check for death date
  FILTER(!BOUND(?deathDate))                 # ensure person is alive
  SERVICE wikibase:label { bd:serviceParam wikibase:language "en" }
  ?person wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel .
  FILTER(LANG(?birthPlaceLabel) = "en")
} ORDER BY ?dateOfBirth
```

Wait! I made a mistake: `SERVICE wikibase:label` is not allowed per the instructions. We must use `rdfs:label` with `FILTER(LANG(?label) = "en")` instead.

Let me correct the query:

```sparql
SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE {
  ?person wdt:P31 wd:Q5 ;                    # is a human
          wdt:P106 wd:Q482980 ;              # occupation: author
          wdt:P27 wd:Q30 ;                   # citizenship: United States
          wdt:P19 wd:Q771 ;                  # birthplace: Massachusetts
          wdt:P569 ?dateOfBirth .            # date of birth
  FILTER(?dateOfBirth >= "1919-12-31T00:00:00Z"^^xsd:dateTime)  # born after 1919
  OPTIONAL { ?person wdt:P570 ?deathDate }   # check for death date
  FILTER(!BOUND(?deathDate))                 # ensure person is alive
  ?person wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel .
  FILTER(LANG(?birthPlaceLabel) = "en")
} ORDER BY ?dateOfBirth
```

We also need to consider that some authors might have `wd:Q36180` (writer) as their occupation. Let's include that too.

### Final SPARQL query:
```sparql
SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE {
  ?person wdt:P31 wd:Q5 ;                    # is a human
          (wdt:P106/wdt:P279*) wd:Q482980 ;  # occupation: author or any subclass
          wdt:P27 wd:Q30 ;                   # citizenship: United States
          wdt:P19 wd:Q771 ;                  # birthplace: Massachusetts
          wdt:P569 ?dateOfBirth .            # date of birth
  FILTER(?dateOfBirth >= "1919-12-31T00:00:00Z"^^xsd:dateTime)  # born after 1919
  OPTIONAL { ?person wdt:P570 ?deathDate }   # check for death date
  FILTER(!BOUND(?deathDate))                 # ensure person is alive
  ?person wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel .
  FILTER(LANG(?birthPlaceLabel) = "en")
} ORDER BY ?dateOfBirth
```

Wait — I used `wdt:P106/wdt:P279*` to include subclasses of "author". But `wdt:P106` is a direct property, and `wdt:P279` is for subclass. We should use `wdt:P106` with `wd:Q482980` or `wd:Q36180`.

Let me simplify and use both occupations explicitly:

```sparql
SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE {
  ?person wdt:P31 wd:Q5 ;                    # is a human
          (wdt:P106/(wdt:P279*)) ?occupation ;
          wdt:P27 wd:Q30 ;                   # citizenship: United States
          wdt:P19 wd:Q771 ;                  # birthplace: Massachusetts
          wdt:P569 ?dateOfBirth .            # date of birth
  FILTER(?dateOfBirth >= "1919-12-31T00:00:00Z"^^xsd:dateTime)  # born after 1919
  OPTIONAL { ?person wdt:P570 ?deathDate }   # check for death date
  FILTER(!BOUND(?deathDate))                 # ensure person is alive
  ?person wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel .
  FILTER(LANG(?birthPlaceLabel) = "en")
  FILTER(?occupation IN (wd:Q482980, wd:Q36180))
} ORDER BY ?dateOfBirth
```

Actually, `wdt:P106` is direct, so we can just use `wdt:P106` with `wd:Q482980` or `wd:Q36180`:

```sparql
SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE {
  ?person wdt:P31 wd:Q5 ;                    # is a human
          wdt:P106 ?occupation ;
          wdt:P27 wd:Q30 ;                   # citizenship: United States
          wdt:P19 wd:Q771 ;                  # birthplace: Massachusetts
          wdt:P569 ?dateOfBirth .            # date of birth
  FILTER(?dateOfBirth >= "1919-12-31T00:00:00Z"^^xsd:dateTime)  # born after 1919
  OPTIONAL { ?person wdt:P570 ?deathDate }   # check for death date
  FILTER(!BOUND(?deathDate))                 # ensure person is alive
  ?person wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel .
  FILTER(LANG(?birthPlaceLabel) = "en")
  FILTER(?occupation IN (wd:Q482980, wd:Q36180))
} ORDER BY ?dateOfBirth
```

This should be correct.

### Step 7: Execute the query
Let's execute the query to see if it returns results.

execute

SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE { ?person wdt:P31 wd:Q5 ; wdt:P106 ?occupation ; wdt:P27 wd:Q30 ; wdt:P19 wd:Q771 ; wdt:P569 ?dateOfBirth . FILTER(?dateOfBirth >= "1919-12-31T00:00:00Z"^^xsd:dateTime) OPTIONAL { ?person wdt:P570 ?deathDate } FILTER(!BOUND(?deathDate)) ?person wdt:P19 ?birthPlace . ?birthPlace rdfs:label ?birthPlaceLabel . FILTER(LANG(?birthPlaceLabel) = "en") FILTER(?occupation IN (wd:Q482980, wd:Q36180)) } ORDER BY ?dateOfBirth

Got 25 rows and 3 columns, showing the first 5 and last 5 rows below:
| person                              | dateOfBirth                         | birthPlaceLabel         |
| ----------------------------------- | ----------------------------------- | ----------------------- |
| Joan Larkin (wd:Q13563279)          | 1939-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Sara Pennypacker (wd:Q7421740)      | 1951-12-09T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Dara Joy (wd:Q20497946)             | 1952-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Michael Tonello (wd:Q6834918)       | 1958-07-19T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Suzanne Strempek Shea (wd:Q7650975) | 1958-12-07T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| ...                                 | ...                                 | ...                     |
| Sarah Manguso (wd:Q2224436)         | 1974-02-12T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Jason M. Burns (wd:Q6163000)        | 1978-03-17T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Sarah Jaffe (wd:Q55617913)          | 1980-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Haroon Moghul (wd:Q16203638)        | 1980-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |
| Wu Tsang (wd:Q17581477)             | 1982-01-01T00:00:00Z (xsd:dateTime) | Massachusetts (lang:en) |

[Assistant]
The query successfully returned 25 living authors who are U.S. citizens, born in Massachusetts after 1919, with their birthplace and date of birth, ordered by date of birth. The results include notable authors such as Joan Larkin (born 1939), Sara Pennypacker (born 1951), and Wu Tsang (born 1982), all with birthplace labeled as "Massachusetts" in English.

### Final Answer:
The SPARQL query correctly retrieves the requested information. Here is the final answer:

```sparql
SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE {
  ?person wdt:P31 wd:Q5 ;                    # is a human
          wdt:P106 ?occupation ;
          wdt:P27 wd:Q30 ;                   # citizenship: United States
          wdt:P19 wd:Q771 ;                  # birthplace: Massachusetts
          wdt:P569 ?dateOfBirth .            # date of birth
  FILTER(?dateOfBirth >= "1919-12-31T00:00:00Z"^^xsd:dateTime)  # born after 1919
  OPTIONAL { ?person wdt:P570 ?deathDate }   # check for death date
  FILTER(!BOUND(?deathDate))                 # ensure person is alive
  ?person wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel .
  FILTER(LANG(?birthPlaceLabel) = "en")
  FILTER(?occupation IN (wd:Q482980, wd:Q36180))
} ORDER BY ?dateOfBirth
```

The results show 25 living authors meeting the criteria, with birthplace as "Massachusetts" and dates of birth from 1939 to 1982.

answer(kg="wikidata", sparql="SELECT ?person ?dateOfBirth ?birthPlaceLabel WHERE { ?person wdt:P31 wd:Q5 ; wdt:P106 ?occupation ; wdt:P27 wd:Q30 ; wdt:P19 wd:Q771 ; wdt:P569 ?dateOfBirth . FILTER(?dateOfBirth >= \"1919-12-31T00:00:00Z\"^^xsd:dateTime) OPTIONAL { ?person wdt:P570 ?deathDate } FILTER(!BOUND(?deathDate)) ?person wdt:P19 ?birthPlace . ?birthPlace rdfs:label ?birthPlaceLabel . FILTER(LANG(?birthPlaceLabel) = \"en\") FILTER(?occupation IN (wd:Q482980, wd:Q36180)) } ORDER BY ?dateOfBirth", answer="There are 25 living authors who are citizens of the United States, were born in Massachusetts after 1919. Their birthplace is Massachusetts, and their dates of birth range from 1939 to 1982. Examples include Joan Larkin (born 1939), Sara Pennypacker (born 1951), and Wu Tsang (born 1982).")