Triple
T29037981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WrestleMania 36 |
E737916
|
entity |
| Predicate | universalTitleMatchWinner |
P51199
|
FINISHED |
| Object | Braun Strowman |
—
|
NE NERFINISHED |
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: Braun Strowman | Statement: [WrestleMania 36, universalTitleMatchWinner, Braun Strowman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: universalTitleMatchWinner Context triple: [WrestleMania 36, universalTitleMatchWinner, Braun Strowman]
-
A.
winnerNickname
Indicates the nickname used to refer to the entity that has won a particular contest, event, or competition.
-
B.
winnerTitle
Indicates the formal title or designation awarded to the entity that wins a particular competition, contest, or event.
-
C.
featuredMatchWinner
chosen
Indicates that an entity is the winner of a highlighted or prominently featured match.
-
D.
unificationMatchWinner
Indicates that an entity is the winner of a unification match between two or more competing entities.
-
E.
universalTitleMatch
Indicates that two entities share exactly the same title string across all considered contexts or sources.
- 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_69f077efb3848190b41574e1670f6ae2 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f66d7765208190b87b1cc6d96a151c |
completed | May 2, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 10 a.m.