Triple
T409740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bobby Charlton |
E9462
|
entity |
| Predicate | nationalTeamAppearances |
P13109
|
FINISHED |
| Object | 106 for 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: 106 for England | Statement: [Bobby Charlton, nationalTeamAppearances, 106 for England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalTeamAppearances Context triple: [Bobby Charlton, nationalTeamAppearances, 106 for England]
-
A.
nationalFootballTeam
Indicates that one entity is the official football (soccer) team representing the other entity at the national level.
-
B.
mostTeamsInCountry
Indicates that an entity has the highest number of teams located within a given country compared to all other entities.
-
C.
nationalCaps
Indicates that one entity serves as the national capital city of another entity (typically a country or nation).
-
D.
teamPlayedFor
Indicates that a person was a member of and played for a particular sports team.
-
E.
allStarAppearances
Indicates the number of times an entity has been selected to participate in an All-Star event or game.
- 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.