Triple
T29037986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WrestleMania 36 |
E737916
|
entity |
| Predicate | matchesPreTaped |
P165955
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [WrestleMania 36, matchesPreTaped, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matchesPreTaped Context triple: [WrestleMania 36, matchesPreTaped, yes]
-
A.
matchesType
Indicates that one entity has the same or a compatible type as another entity according to a defined type system or classification.
-
B.
matcher
Indicates that one entity corresponds to, aligns with, or is considered an appropriate or equivalent counterpart to another entity based on specified criteria.
-
C.
mayMatch
Indicates a potential or permissible correspondence or pairing between two entities, without guaranteeing that the match actually occurs.
-
D.
includesMatch
Indicates that one entity contains or encompasses a particular match or matching instance of another entity.
-
E.
matchType
Indicates the specific category or nature of how two or more entities correspond or align with each other within a given context.
- 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_69f077efb3848190b41574e1670f6ae2 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f6603e70308190a25e074c705d1cb0 |
completed | May 2, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69f659d297cc8190b2b962ba30a1edb3 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65ad638ac8190a17bb987fce53279 |
completed | May 2, 2026, 8:13 p.m. |
Created at: April 28, 2026, 10 a.m.