Triple
T35805411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Batista vs Triple H |
E1035089
|
entity |
| Predicate | firstMajorMatchLoser |
P43689
|
FINISHED |
| Object | Triple H |
E318025
|
NE 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: Triple H | Statement: [Batista vs Triple H, firstMajorMatchLoser, Triple H]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMajorMatchLoser Context triple: [Batista vs Triple H, firstMajorMatchLoser, Triple H]
-
A.
thirdMajorMatchLoser
Indicates that the subject is the competitor who lost in the third major match of a series or tournament.
-
B.
thirdMajorMatchWinner
Indicates that the subject is the winner of the third major match in a specified series or competition.
-
C.
featuredMatchLoser
Indicates that an entity is the participant who lost in a designated featured match.
-
D.
finalBoutLoser
Indicates that an entity is the competitor who lost in the final bout of a match, tournament, or competition.
-
E.
firstGameLoser
chosen
Indicates that the referenced entity is the one who lost the first game in a series, match, or competition.
- F. None of above.
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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38d522a9e08190b2ca9832884b1428 |
completed | June 22, 2026, 6:24 a.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.