Triple
T485549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eric Cantona |
E9867
|
entity |
| Predicate | numberOfInternationalGoals |
P9098
|
FINISHED |
| Object | 20 |
—
|
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: 20 | Statement: [Eric Cantona, numberOfInternationalGoals, 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfInternationalGoals Context triple: [Eric Cantona, numberOfInternationalGoals, 20]
-
A.
numberOfGoals
chosen
Indicates the total count of goals scored or achieved by an entity in a given context.
-
B.
nationalTeamAppearances
Indicates the number of official matches in which an entity has represented its national team.
-
C.
keyInternationalOpponent
Indicates that one entity is a primary or significant adversary or rival of another in an international context.
-
D.
goalScorer
Indicates that the subject is the player who scored a particular goal in a game or match.
-
E.
hasPlayedInCountry
Indicates that an entity (typically a person or team) has participated in a game, match, or performance within a specified country.
- 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_69a2e802e2908190ab17c9479e0b6412 |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0bb46788190b40182bf2a54f98f |
completed | Feb. 28, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69a2edf48ec08190b85d07e194f99c49 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.