Triple
T29906439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico vs Cameroon (2014 FIFA World Cup) |
E759547
|
entity |
| Predicate | homeTeamGoalsInFirstHalf |
P25688
|
FINISHED |
| Object | 0 |
—
|
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: 0 | Statement: [Mexico vs Cameroon (2014 FIFA World Cup), homeTeamGoalsInFirstHalf, 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeTeamGoalsInFirstHalf Context triple: [Mexico vs Cameroon (2014 FIFA World Cup), homeTeamGoalsInFirstHalf, 0]
-
A.
homeTeamGoalsFirstHalf
chosen
Indicates the number of goals scored by the home team during the first half of a match.
-
B.
awayTeamGoalsFirstHalf
Indicates the number of goals scored by the away team during the first half of a match.
-
C.
homeTeamPointsInFirstHalf
Indicates the number of points scored by the home team during the first half of a game.
-
D.
homeTeamGoalsSecondHalf
Indicates the number of goals scored by the home team during the second half of a match.
-
E.
awayTeamPointsInFirstHalf
Indicates the number of points scored by the away team during the first half of a game.
- 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_69f224600590819085e148a01c056ef6 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67d3624248190a36a9b2d2e9778d4 |
completed | May 2, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 6:08 p.m.