Triple
T12807209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Rapaport |
E306175
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Big Fan |
E749718
|
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: Big Fan | Statement: [Michael Rapaport, notableWork, Big Fan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Big Fan Context triple: [Michael Rapaport, notableWork, Big Fan]
-
A.
Big Fan
chosen
Big Fan is a dark comedy-drama film about an obsessive New York Giants fan whose life unravels after a violent encounter with his favorite player.
-
B.
The Fan
The Fan is a 1996 psychological thriller film about an obsessive baseball fan whose fixation on his favorite player turns dangerously violent.
-
C.
The Fan
The Fan is the popular nickname for Beijing's National Indoor Stadium, a major multi-purpose arena known for hosting events during the 2008 and 2022 Olympic Games.
-
D.
Fan y Big
Fan y Big is a prominent peak in the central Brecon Beacons of South Wales, known for its distinctive cliffs and panoramic views.
-
E.
Fanatikerne
Fanatikerne is a notable painting by Norwegian artist Adolph Tidemand depicting religious zealots in a dramatic, realist style.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e808130819080f404b3a7462c2e |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ec6556081909375fada79ddcb8c |
completed | May 2, 2026, 11:54 p.m. |
Created at: April 9, 2026, 5:31 p.m.