Triple
T10277122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miami RedHawks football |
E240995
|
entity |
| Predicate | coachProduced |
P93227
|
FINISHED |
| Object | Sid Gillman |
E560623
|
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: Sid Gillman | Statement: [Miami RedHawks football, coachProduced, Sid Gillman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sid Gillman Context triple: [Miami RedHawks football, coachProduced, Sid Gillman]
-
A.
Sid Gillman
chosen
Sid Gillman was an innovative American football coach and Hall of Famer widely regarded as a pioneer of the modern passing offense.
-
B.
Elmore Brooks
Elmore Brooks, better known as Elmore James, was an influential American blues guitarist, singer, and songwriter celebrated as the "King of the Slide Guitar."
-
C.
Larry Eigner
Larry Eigner was an American poet associated with the Black Mountain and Language poetry movements, known for his visually spaced, minimalist verse often composed from his wheelchair.
-
D.
Harold Greene
Harold Greene was a Hollywood screenwriter active in the early 20th century, known for his work on classic studio-era films.
-
E.
Fritz Lanman
Fritz Lanman is an American technology executive and investor known for his leadership roles at companies like ClassPass and his early investment in and involvement with startups such as Square.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4dfbfa26c8190b536655d33112ddf |
completed | April 7, 2026, 10:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f82188588190998e06cad1e15e68 |
completed | April 9, 2026, 12:51 a.m. |
Created at: April 6, 2026, 11:37 a.m.