Triple
T945909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaws (novel) |
E20412
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Matt Hooper |
E20945
|
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: Matt Hooper | Statement: [Jaws (novel), character, Matt Hooper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Hooper Context triple: [Jaws (novel), character, Matt Hooper]
-
A.
Matt Hooper
chosen
Matt Hooper is the marine biologist in the film "Jaws" who helps hunt the great white shark terrorizing Amity Island.
-
B.
Matt Kowalski
Matt Kowalski is a veteran NASA astronaut and spacewalker featured as a central character in the science fiction film "Gravity."
-
C.
Paul Griffin
Paul Griffin was an American session keyboardist renowned for his soulful, inventive playing on landmark recordings by artists such as Bob Dylan, Steely Dan, and countless others.
-
D.
John Eden
John Eden is a British Conservative politician who served in senior government roles, including as a cabinet minister in the mid-20th century.
-
E.
Michael V. Drake
Michael V. Drake is an American academic leader and physician who has served as president of both The Ohio State University and the University of California system.
- 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_69a493b0f2fc81908cd227480a5356a1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3a61b648190b1b6c932e047e161 |
completed | March 1, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a826e7d55c8190b9b871caead76733 |
completed | March 4, 2026, 12:34 p.m. |
Created at: March 1, 2026, 7:40 p.m.