Triple
T468561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Best |
E8503
|
entity |
| Predicate | positionPlayedOnTeam |
P11645
|
FINISHED |
| Object | winger |
—
|
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: winger | Statement: [George Best, positionPlayedOnTeam, winger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionPlayedOnTeam Context triple: [George Best, positionPlayedOnTeam, winger]
-
A.
playsInPosition
Indicates that an entity (typically a player) performs or operates in a specific role or position within a game, sport, or activity.
-
B.
positionPlayedInCollege
Indicates the specific playing position an individual held on a sports team during their college career.
-
C.
teamPlayedFor
Indicates that a person was a member of and played for a particular sports team.
-
D.
playedFor
Indicates that one entity has been a member of or participated as a player for a particular team, organization, or group.
-
E.
playingPosition
chosen
Indicates the specific role or position an individual occupies while participating in a game or sport.
- 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efd9bea081909ee782840f3da12b |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2edebb3988190907992a584b4e260 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.