Triple
T20298117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuns on the Run |
E505405
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Tom Hickey |
—
|
NE NERFINISHED |
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: Tom Hickey | Statement: [Nuns on the Run, hasCastMember, Tom Hickey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Hickey Context triple: [Nuns on the Run, hasCastMember, Tom Hickey]
-
A.
Tom Hickey
chosen
Tom Hickey was an Irish actor known for his extensive work in theatre, film, and television, particularly in Ireland.
-
B.
Nat Hickey
Nat Hickey was an early professional basketball player and coach best known for briefly appearing in an NBA game at age 45, making him the oldest player in league history.
-
C.
Frank Horrigan
Frank Horrigan is a veteran Secret Service agent haunted by his failure to protect President Kennedy, who becomes determined to stop a new presidential assassination plot in the thriller film "In the Line of Fire."
-
D.
Frank Quinlan
Frank Quinlan is a central character in the 1996 fantasy drama film "Michael," portrayed as one of the reporters who travels with the archangel Michael and documents his unconventional behavior.
-
E.
Tom Henighan
Tom Henighan is a researcher and co-author known for his work in large-scale language models and AI, including contributions to influential OpenAI publications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b8ab648190906e18538c250148 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6770a2cec8190912d6b0dbabc78bc |
completed | April 20, 2026, 6:57 p.m. |
Created at: April 16, 2026, 11:16 a.m.