Triple
T2995224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mindhunters |
E81049
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Neil Farrell |
E260226
|
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: Neil Farrell | Statement: [Mindhunters, editor, Neil Farrell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neil Farrell Context triple: [Mindhunters, editor, Neil Farrell]
-
A.
Neil Farrell
chosen
Neil Farrell is a film editor best known for his work on Kenneth Branagh’s 1996 adaptation of Hamlet.
-
B.
Kevin Rooney
Kevin Rooney is an American boxing trainer best known for coaching Mike Tyson during his rise to the heavyweight championship in the 1980s.
-
C.
Andrew Duggan
Andrew Duggan was an American character actor known for his prolific work in film and television from the 1950s through the 1980s.
-
D.
Daniel Neeson
Daniel Neeson is the son of acclaimed Irish actor Liam Neeson and his late wife, actress Natasha Richardson.
-
E.
Kevin Corrigan
Kevin Corrigan is an American character actor known for his offbeat, often darkly comic supporting roles in numerous independent films and major studio movies.
- 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_69ad8b187fc8819085914d3c9ea3142d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99f2e5888190b3346012e2578dab |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12e3bac408190b09bafee840eb0d1 |
completed | March 11, 2026, 8:56 a.m. |
Created at: March 8, 2026, 2:59 p.m.