Triple
T409744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bobby Charlton |
E9462
|
entity |
| Predicate | teamAchievement |
P13110
|
FINISHED |
| Object | 1966 FIFA World Cup winner with 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: 1966 FIFA World Cup winner with England | Statement: [Bobby Charlton, teamAchievement, 1966 FIFA World Cup winner with England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamAchievement Context triple: [Bobby Charlton, teamAchievement, 1966 FIFA World Cup winner with England]
-
A.
featuredTeam
Indicates that a particular team is highlighted or given special prominence in a given context or presentation.
-
B.
team
Indicates that multiple entities are grouped together as a collaborative unit working toward shared goals or tasks.
-
C.
associatedTeam
Indicates that one entity is linked or connected to a particular team, typically as its member, owner, or primary affiliation.
-
D.
team1
Indicates that the referenced entity is the first team or side participating in a competitive or relational context.
-
E.
topScorerTeam
Indicates that a given team is the one with the highest score (or total points) in a particular game, season, or competition.
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ed31681c8190ac32334562fb17fd |
completed | Feb. 28, 2026, 1:27 p.m. |
| PD | Predicate disambiguation | batch_69a2e9737694819080fde9adcc1aa4d4 |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ed3032148190beb3a516e437f8f8 |
completed | Feb. 28, 2026, 1:27 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.