Triple
T24631315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Just Louis Fontaine |
E609682
|
entity |
| Predicate | numberOfGoalsScoredInTournament |
P9098
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [Just Louis Fontaine, numberOfGoalsScoredInTournament, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGoalsScoredInTournament Context triple: [Just Louis Fontaine, numberOfGoalsScoredInTournament, 13]
-
A.
numberOfGoals
chosen
Indicates the total count of goals scored or achieved by an entity in a given context.
-
B.
scoredGoalsInFinalOf
Indicates that one entity scored one or more goals in the final match of a specified competition or event.
-
C.
scoredInTournament
Indicates that an entity achieved a score or points during a particular tournament.
-
D.
worldCupGoals
Indicates the number of goals an entity scored in World Cup matches.
-
E.
totalPointsScored
Indicates the total number of points accumulated or scored by an entity over a defined period, event, or context.
- 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_69e2c4d1d3708190a0f2dc6a3a8523bb |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be064ff88190b5d9e5ec75a41242 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6d0ab708190b2e3b94dd20ca76b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:32 a.m.