Triple
T1079357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2010 FIFA World Cup |
E23911
|
entity |
| Predicate | openingMatch |
P23679
|
FINISHED |
| Object | South Africa vs 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 vs Mexico | Statement: [2010 FIFA World Cup, openingMatch, South Africa vs Mexico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openingMatch Context triple: [2010 FIFA World Cup, openingMatch, South Africa vs Mexico]
-
A.
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.
-
B.
openingWorkOf
Indicates that one work serves as the first or introductory piece in relation to another work, such as the opening item in a sequence or collection.
-
C.
openingGameCity
Indicates the city where an opening game or initial match of an event takes place.
-
D.
openSeason
Indicates that a period has begun during which a particular activity (such as hunting, fishing, or competition) is officially allowed or actively underway.
-
E.
firstInternationalMatch
Indicates that the match is the first international-level game played by the entity (such as a team or player) in question.
- 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.