Triple
T29710395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germany vs Mexico |
E751761
|
entity |
| Predicate | MexicoWorldCupTitlesBeforeMatch |
P169324
|
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: [Germany vs Mexico, MexicoWorldCupTitlesBeforeMatch, 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MexicoWorldCupTitlesBeforeMatch Context triple: [Germany vs Mexico, MexicoWorldCupTitlesBeforeMatch, 0]
-
A.
BrazilWorldCupTitlesBeforeMatch
Indicates the number of FIFA World Cup titles Brazil had already won prior to the referenced match.
-
B.
homeTeamWorldCupTitlesBeforeMatch
Indicates the number of FIFA World Cup titles the home team had already won prior to the start of the match.
-
C.
WorldCupVictories
Indicates the number of times an entity has won the FIFA World Cup tournament.
-
D.
WorldCupWins
Indicates the number of times an entity (typically a national team) has won the FIFA World Cup tournament.
-
E.
awayTeamWorldCupTitlesBeforeMatch
Indicates the number of World Cup titles the away team had already won prior to the match taking 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_69f0d62748848190b030d0a703629a7d |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f67de7792c81909b5e4e812d143624 |
completed | May 2, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f67d31cc60819084f64bd056e1ea4d |
completed | May 2, 2026, 10:39 p.m. |
Created at: April 28, 2026, 7:30 p.m.