Triple
T33278851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miami Redskins football |
E851981
|
entity |
| Predicate | coachAlumnus |
P177006
|
FINISHED |
| Object | Woody Hayes |
—
|
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: Woody Hayes | Statement: [Miami Redskins football, coachAlumnus, Woody Hayes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coachAlumnus Context triple: [Miami Redskins football, coachAlumnus, Woody Hayes]
-
A.
notableCoachAlumnus
Indicates that a person is a notable former player or trainee of a particular coach.
-
B.
coachOf
Indicates that one entity serves as the coach (trainer or manager) of another entity, typically a person or team.
-
C.
featuredCoach
Indicates that a particular coach is highlighted or given special prominence within a specific context or collection.
-
D.
coachProfession
Indicates that one entity serves professionally as a coach in relation to the other entity.
-
E.
coachedAthletesAt
Indicates a relationship where a coach has trained or instructed athletes at a particular organization, team, or location.
- F. None of above. chosen
Provenance (4 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_69f349653da08190819876015a298fdb |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6f85bfba48190aba95b40642a8ca7 |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f6619404819084662aef1238261c |
completed | May 3, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69f6f814fcf48190ae4504154d1b2c05 |
completed | May 3, 2026, 7:24 a.m. |
Created at: May 1, 2026, 1:32 a.m.