Triple
T20738625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trent Richardson |
E509778
|
entity |
| Predicate | nationalTitlesWonInCollegeFootball |
P66087
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Trent Richardson, nationalTitlesWonInCollegeFootball, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalTitlesWonInCollegeFootball Context triple: [Trent Richardson, nationalTitlesWonInCollegeFootball, 2]
-
A.
FAcupTitles
Indicates that an entity has won a specified number of FA Cup titles.
-
B.
nationalChampionshipTitle
Indicates that an entity has won a national-level championship title in a particular sport, competition, or field.
-
C.
nationalChampionshipParticipation
Indicates that an entity has taken part in a national-level championship competition.
-
D.
footballNationalChampionshipLevel
Indicates the competitive tier or division at which a football national championship is contested or recognized.
-
E.
numberOfNationalChampionships
chosen
Indicates the total count of national championship titles an entity has won.
- 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_69e0b4c589c08190834fb5d86d0efa2b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c20c36708190898b889b6989fc7d |
completed | April 21, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69e5c04b31248190b9b9d91b5cb854e3 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:32 p.m.