Triple
T13392602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Four Mothers |
E319612
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Philip G. Epstein |
E131782
|
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: Philip G. Epstein | Statement: [Four Mothers, screenwriter, Philip G. Epstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Philip G. Epstein Context triple: [Four Mothers, screenwriter, Philip G. Epstein]
-
A.
Philip G. Epstein
chosen
Philip G. Epstein was an American screenwriter best known for co-writing the classic 1942 film "Casablanca," for which he won an Academy Award.
-
B.
Paul S. Epstein
Paul S. Epstein was a theoretical physicist known for his contributions to early quantum theory and the application of quantum mechanics to atomic and molecular spectra.
-
C.
Paul Epstein
Paul Epstein is a mathematician best known for his work on number theory and contributions related to the Riemann zeta function.
-
D.
Philip Epstein
Philip Epstein was an American screenwriter best known for co-writing the classic film "Casablanca."
-
E.
Ben Epstein
Ben Epstein is an ambitious young New Yorker and aspiring fashion entrepreneur who serves as one of the central protagonists in the HBO series "How to Make It in America."
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dba0d74e5881909828854bba7d9a87 |
completed | April 12, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f72693a440819095a3136d8f49680a |
completed | May 3, 2026, 10:42 a.m. |
Created at: April 9, 2026, 9:34 p.m.