Triple
T6648977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Just Fontaine |
E150770
|
entity |
| Predicate | worldCupGoalsRecord |
P43244
|
FINISHED |
| Object | most goals in a single FIFA World Cup tournament |
—
|
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: most goals in a single FIFA World Cup tournament | Statement: [Just Fontaine, worldCupGoalsRecord, most goals in a single FIFA World Cup tournament]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldCupGoalsRecord Context triple: [Just Fontaine, worldCupGoalsRecord, most goals in a single FIFA World Cup tournament]
-
A.
worldCupGoals
Indicates the number of goals an entity scored in World Cup matches.
-
B.
worldCupRecord
chosen
Indicates a relationship that specifies an entity’s performance statistics or achievements in FIFA World Cup competitions.
-
C.
worldCupHatTricks
Indicates that a player has scored three or more goals in a single FIFA World Cup match.
-
D.
rankAllTimeGoals
Indicates a relationship that orders entities based on the total number of goals they have scored across all time.
-
E.
totalGoalsRecord
Indicates the total number of goals that have been recorded for an entity across all relevant events or contexts.
- 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_69c687f1a3048190828b7342f7125d5c |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6ad04d66c8190926ffcbff372643b |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:01 p.m.