Triple
T18548191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom O’Brien |
E453292
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Tom O’Brien |
—
|
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 O’Brien | Statement: [Tom O’Brien, name, Tom O’Brien]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom O’Brien Context triple: [Tom O’Brien, name, Tom O’Brien]
-
A.
Tom O’Brien
Tom O’Brien is an American football coach best known for revitalizing Boston College’s football program in the late 1990s and early 2000s before later leading NC State.
-
B.
Tom O’Brien
Tom O’Brien was an American actor best known for his roles in silent-era films, including prominent appearances in major 1920s productions.
-
C.
Tom O'Brien
Tom O'Brien is a media executive and broadcaster best known for his leadership and on-air roles at The Weather Channel.
-
D.
John M. Keane
John M. Keane is a television and film composer best known for scoring crime drama series such as CSI: Vegas.
-
E.
John E. Keane
John E. Keane is a composer best known for his work on film and television scores, including the adaptation of "Wives and Daughters."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d8d388b0c881908e610a1c45b52640 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e534be2298819095f637065fc2724e |
completed | April 19, 2026, 8:02 p.m. |
Created at: April 10, 2026, 11:38 a.m.