Triple
T10323372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swimfan |
E242694
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Gale Anne Hurd |
E116019
|
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: Gale Anne Hurd | Statement: [Swimfan, producer, Gale Anne Hurd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gale Anne Hurd Context triple: [Swimfan, producer, Gale Anne Hurd]
-
A.
Gale Anne Hurd
chosen
Gale Anne Hurd is an American film and television producer best known for her influential work on science fiction and action franchises such as The Terminator and Aliens.
-
B.
Callie Khouri
Callie Khouri is an American screenwriter and director best known for her Oscar-winning feminist road movie "Thelma & Louise."
-
C.
Julie Corman
Julie Corman is an American film producer known for her work on low-budget genre films and for collaborating on numerous projects associated with the New World Pictures legacy.
-
D.
Diane Becker
Diane Becker is a film producer best known for her work on the Oscar-winning documentary "Navalny," which chronicles Russian opposition leader Alexei Navalny.
-
E.
Amanda Silver
Amanda Silver is an American screenwriter and producer best known for co-writing major blockbuster films such as Jurassic World and the Avatar sequels.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d6cdb6cc8190b37ca4494287128b |
completed | April 7, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71da2053481908fe5ed097b480cdd |
completed | April 9, 2026, 3:31 a.m. |
Created at: April 6, 2026, 11:50 a.m.