Triple
T14430653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Raynor |
E357817
|
entity |
| Predicate | sportingDisciplineCoached |
P37014
|
FINISHED |
| Object | men's association football |
—
|
LITERAL 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: men's association football | Statement: [George Raynor, sportingDisciplineCoached, men's association football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportingDisciplineCoached Context triple: [George Raynor, sportingDisciplineCoached, men's association football]
-
A.
sportsDisciplineCoachedOrManaged
chosen
Indicates that a person has coached or managed a particular sports discipline or type of sport.
-
B.
hasCoachedDiscipline
Indicates that a person has coached or provided training in a particular discipline, field, or area of expertise.
-
C.
hasCoachedFor
Indicates that one entity has served in a coaching role for another entity, such as a team, organization, or individual.
-
D.
coachedAthletesAt
Indicates a relationship where a coach has trained or instructed athletes at a particular organization, team, or location.
-
E.
coachOf
Indicates that one entity serves as the coach (trainer or manager) of another entity, typically a person or team.
- F. None of above.
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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de914570f08190b1c7c1c57a0cb476 |
completed | April 14, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69de5c30467881908e770e3940295641 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:18 a.m.