Triple
T11447313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Feig |
E271298
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Paul Feig |
E271298
|
NE FINISHED |
How this triple was built (2 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 Feig | Statement: [Paul Feig, name, Paul Feig]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Feig Context triple: [Paul Feig, name, Paul Feig]
-
A.
Paul Feig
chosen
Paul Feig is an American filmmaker, producer, and actor best known for directing hit comedies such as "Bridesmaids" and creating the cult TV series "Freaks and Geeks."
-
B.
Paul Feigay
Paul Feigay is a theatrical producer known for his work on the classic Broadway musical "On the Town."
-
C.
Carol Holofcener
Carol Holofcener is the mother of American film director and screenwriter Nicole Holofcener.
-
D.
Anna Boden
Anna Boden is an American filmmaker best known for co-directing the Marvel Studios superhero film "Captain Marvel" and for her long-time creative partnership with Ryan Fleck on independent dramas.
-
E.
Charlotte Wells
Charlotte Wells is a central courtesan character in the British period drama series "Harlots," known for navigating the power struggles and personal conflicts within 18th-century London's sex trade.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d81c6d4890819082fb4a670feb2629 |
completed | April 9, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5d3bdafb08190aadf5d63facfedaf |
completed | April 20, 2026, 7:20 a.m. |
Created at: April 8, 2026, 9:35 p.m.