Triple
T1820863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | On the Town |
E40535
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Paul Feigay
Paul Feigay is a theatrical producer known for his work on the classic Broadway musical "On the Town."
|
E202817
|
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: Paul Feigay | Statement: [On the Town, producer, Paul Feigay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Feigay Context triple: [On the Town, producer, Paul Feigay]
-
A.
Rainey Reitman
Rainey Reitman is a digital rights and civil liberties advocate known for her leadership roles in organizations defending press freedom and online privacy.
-
B.
Robin Swicord
Robin Swicord is an American screenwriter and director known for her literary adaptations, including films such as Little Women (1994), Memoirs of a Geisha, and The Curious Case of Benjamin Button.
-
C.
Amy Kaufman
Amy Kaufman is a film producer best known for her work on critically acclaimed independent dramas such as "Beasts of No Nation."
-
D.
Jill Hornor
Jill Hornor is an art consultant and the longtime wife of renowned cellist Yo-Yo Ma.
-
E.
Lee Russell
Lee Russell was an American photographer known for his work documenting rural life and poverty in the United States as part of the Farm Security Administration project during the Great Depression.
- 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: Paul Feigay Triple: [On the Town, producer, Paul Feigay]
Generated description
Paul Feigay is a theatrical producer known for his work on the classic Broadway musical "On the Town."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Paul Feigay Target entity description: Paul Feigay is a theatrical producer known for his work on the classic Broadway musical "On the Town."
-
A.
Rainey Reitman
Rainey Reitman is a digital rights and civil liberties advocate known for her leadership roles in organizations defending press freedom and online privacy.
-
B.
Robin Swicord
Robin Swicord is an American screenwriter and director known for her literary adaptations, including films such as Little Women (1994), Memoirs of a Geisha, and The Curious Case of Benjamin Button.
-
C.
Amy Kaufman
Amy Kaufman is a film producer best known for her work on critically acclaimed independent dramas such as "Beasts of No Nation."
-
D.
Jill Hornor
Jill Hornor is an art consultant and the longtime wife of renowned cellist Yo-Yo Ma.
-
E.
Lee Russell
Lee Russell was an American photographer known for his work documenting rural life and poverty in the United States as part of the Farm Security Administration project during the Great Depression.
- 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_69a8864526c081908a3a4d74f689e2c5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa662a13208190b4126d92c613760d |
completed | March 6, 2026, 5:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adbf6526f88190907de68a5344a084 |
completed | March 8, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69adbff32038819088dffc71e8376821 |
completed | March 8, 2026, 6:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adc084c9b88190a0d53f5c7c459611 |
completed | March 8, 2026, 6:31 p.m. |
Created at: March 4, 2026, 7:32 p.m.