Triple
T3659005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Fisher King |
E77603
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Lynda Obst |
E159259
|
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: Lynda Obst | Statement: [The Fisher King, producer, Lynda Obst]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lynda Obst Context triple: [The Fisher King, producer, Lynda Obst]
-
A.
Lynda Obst
chosen
Lynda Obst is an American film producer and author known for her work on major Hollywood films, including the science fiction epic "Interstellar."
-
B.
Lynda Resnick
Lynda Resnick is an American billionaire businesswoman and philanthropist known for co-owning The Wonderful Company and for her extensive arts and cultural patronage.
-
C.
Joely Richardson
Joely Richardson is an English actress known for her work in film and television, including roles in projects such as "Nip/Tuck" and various period dramas.
-
D.
Tyne Daly
Tyne Daly is an American actress acclaimed for her powerful performances in television dramas, film, and theater, including her iconic role in the series "Cagney & Lacey."
-
E.
Lynda Dryden
Lynda Dryden is the wife of former NHL goaltender and Canadian politician Ken Dryden.
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3d48a2081908ac0f76d548a53ee |
completed | March 8, 2026, 6:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b48842b28881908c6a077cfaa8b092 |
completed | March 13, 2026, 9:57 p.m. |
Created at: March 8, 2026, 3:25 p.m.