Triple
T1079358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2010 FIFA World Cup |
E23911
|
entity |
| Predicate | openingMatchScore |
P23680
|
FINISHED |
| Object | South Africa 1–1 Mexico |
—
|
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: South Africa 1–1 Mexico | Statement: [2010 FIFA World Cup, openingMatchScore, South Africa 1–1 Mexico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openingMatchScore Context triple: [2010 FIFA World Cup, openingMatchScore, South Africa 1–1 Mexico]
-
A.
firstInternationalMatch
Indicates that the match is the first international-level game played by the entity (such as a team or player) in question.
-
B.
openingTheme
Indicates that one entity serves as the opening theme (such as a song or musical piece) for another entity, typically a show, series, or similar work.
-
C.
firstGamePlayed
Indicates the specific game that an entity participated in before any other, marking the earliest game in which it played.
-
D.
firstGameOpponent
Indicates that one entity is the opponent faced by another entity in its first game or match.
-
E.
openingGameCity
Indicates the city where an opening game or initial match of an event takes place.
- F. None of above. chosen
Provenance (4 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b94509d08190964509ea4a2d7912 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b73d9f08819093668104f129840e |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b80f0fb08190a19a50e38ae8f16c |
completed | March 1, 2026, 10:05 p.m. |
Created at: March 1, 2026, 7:42 p.m.