Triple
T2646452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Tierney |
E53794
|
entity |
| Predicate | sportNumberOfClubs |
P41025
|
FINISHED |
| Object | 1 (senior professional club) |
—
|
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: 1 (senior professional club) | Statement: [Chris Tierney, sportNumberOfClubs, 1 (senior professional club)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportNumberOfClubs Context triple: [Chris Tierney, sportNumberOfClubs, 1 (senior professional club)]
-
A.
leagueOwned
Indicates that a league has ownership or controlling rights over the referenced entity.
-
B.
associationFootballClub
Indicates that the subject is an association football (soccer) club, i.e., an organized team entity that plays the sport of association football.
-
C.
eligibleClubs
Indicates that certain clubs meet the required criteria or conditions to qualify for a specified status, activity, or benefit.
-
D.
associatedWithFootballClub
Indicates that there is a relationship of affiliation or connection between an entity and a football club.
-
E.
leagueOfAcquiredClub
Indicates that a club has been acquired by an entity and specifies the league in which that acquired club competes.
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd91846b4819093a063c15e1ee6af |
completed | March 7, 2026, 7:51 a.m. |
| PD | Predicate disambiguation | batch_69abd814298c8190952f05aed43f6bb8 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd879bb808190bd2c34de1664c816 |
completed | March 7, 2026, 7:49 a.m. |
Created at: March 6, 2026, 9:53 p.m.