Triple
T6673805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harvey |
E151799
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Marya Z. Wolf
Marya Z. Wolf is a screenwriter known for her work on the film "Harvey."
|
E611048
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Marya Z. Wolf | Statement: [Harvey, screenwriter, Marya Z. Wolf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marya Z. Wolf Context triple: [Harvey, screenwriter, Marya Z. Wolf]
-
A.
Anna D. Shapiro
Anna D. Shapiro is a Tony Award–winning American theater director known for her work on major Broadway productions and new plays.
-
B.
Emily T. Troscianko
Emily T. Troscianko is a scholar and writer known for her work on consciousness studies and the psychology of reading, including co-authoring the textbook "Consciousness: An Introduction."
-
C.
Sonya Walger
Sonya Walger is a British actress best known for her roles in television series such as "Lost," "FlashForward," and "For All Mankind."
-
D.
Susanne C. Brenner
Susanne C. Brenner is an American mathematician known for her contributions to numerical analysis and finite element methods.
-
E.
Alice Dannenberg
Alice Dannenberg was a Russian-born French painter and influential art teacher best known as a co-founder of the progressive Parisian art school Académie de la Grande Chaumière.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Marya Z. Wolf Triple: [Harvey, screenwriter, Marya Z. Wolf]
Generated description
Marya Z. Wolf is a screenwriter known for her work on the film "Harvey."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marya Z. Wolf Target entity description: Marya Z. Wolf is a screenwriter known for her work on the film "Harvey."
-
A.
Anna D. Shapiro
Anna D. Shapiro is a Tony Award–winning American theater director known for her work on major Broadway productions and new plays.
-
B.
Emily T. Troscianko
Emily T. Troscianko is a scholar and writer known for her work on consciousness studies and the psychology of reading, including co-authoring the textbook "Consciousness: An Introduction."
-
C.
Sonya Walger
Sonya Walger is a British actress best known for her roles in television series such as "Lost," "FlashForward," and "For All Mankind."
-
D.
Susanne C. Brenner
Susanne C. Brenner is an American mathematician known for her contributions to numerical analysis and finite element methods.
-
E.
Alice Dannenberg
Alice Dannenberg was a Russian-born French painter and influential art teacher best known as a co-founder of the progressive Parisian art school Académie de la Grande Chaumière.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b0f1d9d081909670f5c0b7389c0d |
completed | March 27, 2026, 4:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f7a10ec08190983a66b874a1d541 |
completed | March 27, 2026, 9:33 p.m. |
| NEDg | Description generation | batch_69c6f8d27d388190816cfeefbe1519d8 |
completed | March 27, 2026, 9:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6f96c215081909e9d7a6e0a811f18 |
completed | March 27, 2026, 9:41 p.m. |
Created at: March 27, 2026, 2:03 p.m.