Triple
T8089663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dwight Gayle |
E188823
|
entity |
| Predicate | hasPlayedForYouthOrLowerLeagues |
P8948
|
FINISHED |
| Object | non-league football in England |
—
|
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: non-league football in England | Statement: [Dwight Gayle, hasPlayedForYouthOrLowerLeagues, non-league football in England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlayedForYouthOrLowerLeagues Context triple: [Dwight Gayle, hasPlayedForYouthOrLowerLeagues, non-league football in England]
-
A.
playedForJuniorTeam
chosen
Indicates that an individual was a member of and played for a specific junior-level sports team.
-
B.
hasYouthTeam
Indicates that an entity has an associated youth team that serves as its junior or developmental squad.
-
C.
hasExperienceInLeague
Indicates that an entity has previously participated or been involved in a particular league.
-
D.
hasNonLeagueFootballHistory
Indicates that an entity has a history of participation in football competitions outside the official league system.
-
E.
hasSeniorClubExperience
Indicates that an individual has played for or been a member of a senior-level (adult/professional) sports club.
- 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_69ca82b7b3e88190b9041ab0ef28b3cb |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb421e30e88190b9699b338b69b81c |
completed | March 31, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:29 p.m.