Triple
T13510132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Contact |
E321116
|
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: [Contact, producer, Lynda Obst]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lynda Obst Context triple: [Contact, 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 Bernhard
Lynda Bernhard is known as the wife of American film producer Harvey Bernhard.
-
C.
Lucinda Jenney
Lucinda Jenney is an American character actress known for her versatile supporting roles in films and television since the 1980s.
-
D.
Lynda Petty
Lynda Petty was the longtime wife of NASCAR legend Richard Petty and a prominent figure in the racing community known for her charitable work and support of the Petty family’s motorsports legacy.
-
E.
Lisa Reisert
Lisa Reisert is the resourceful and determined protagonist of the thriller film "Red Eye," who becomes entangled in a high-stakes assassination plot during a red-eye flight.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf86a6208190be8c18f7a0158f23 |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d9009688190b8f18bb3525c6afd |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:43 p.m.