Triple
T24422704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France vs Mexico (1930 FIFA World Cup) |
E615766
|
entity |
| Predicate | goalScorerForFrance |
P2695
|
FINISHED |
| Object | Lucien Laurent |
—
|
NE NERFINISHED |
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: Lucien Laurent | Statement: [France vs Mexico (1930 FIFA World Cup), goalScorerForFrance, Lucien Laurent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goalScorerForFrance Context triple: [France vs Mexico (1930 FIFA World Cup), goalScorerForFrance, Lucien Laurent]
-
A.
goalsForFrance
Indicates that the subject scored a goal while playing for the France national team.
-
B.
goalScorer
chosen
Indicates that the subject is the player who scored a particular goal in a game or match.
-
C.
finalGoalscorer
Indicates that an entity is the player who scored the last goal in a particular match or event.
-
D.
previousFranceWorldCupTitleYear
Indicates the year in which France most recently won the FIFA World Cup prior to a given reference point.
-
E.
opponentInEuro2016Final
Indicates that one entity was the opposing team of the other entity in the final match of the UEFA Euro 2016 tournament.
- 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_69e2d7eadb248190a867130fe45f0388 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f296a4285881909376560f1cf4bf62 |
completed | April 29, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69f287cc4fd4819081e93cc638d9512d |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:14 a.m.