Triple
T29378388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nigeria vs Argentina (2018 FIFA World Cup Group D) |
E745065
|
entity |
| Predicate | equalisingGoalType |
P72446
|
FINISHED |
| Object | penalty kick |
—
|
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: penalty kick | Statement: [Nigeria vs Argentina (2018 FIFA World Cup Group D), equalisingGoalType, penalty kick]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equalisingGoalType Context triple: [Nigeria vs Argentina (2018 FIFA World Cup Group D), equalisingGoalType, penalty kick]
-
A.
equalizingGoalBy
Indicates that one entity has the objective of reducing differences or disparities between itself and another entity.
-
B.
equalisingGoalTeam
Indicates that a team scores a goal which brings the score level with the opposing team.
-
C.
winningGoalType
Indicates the specific manner or category of the goal that determined the final victory in a competition or match.
-
D.
goalType
chosen
Indicates the specific category or nature of a goal associated with an entity or action.
-
E.
equaliserType
Indicates that one entity specifies or classifies the type or category of equaliser associated with another entity.
- 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_69f0a79cfd5481909b4dde750cb8d2c6 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 28, 2026, 2:33 p.m.