Triple
T35679491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OVW Women’s Championship |
E1030964
|
entity |
| Predicate | hasMatchTypes |
P132627
|
FINISHED |
| Object | singles matches |
—
|
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: singles matches | Statement: [OVW Women’s Championship, hasMatchTypes, singles matches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMatchTypes Context triple: [OVW Women’s Championship, hasMatchTypes, singles matches]
-
A.
hasTypeOfMatches
chosen
Indicates that one entity has matches that are of a specified type or category in relation to another entity.
-
B.
matchTypes
Indicates that two or more entities share the same type or category according to a specified classification.
-
C.
matchesType
Indicates that one entity has the same or a compatible type as another entity according to a defined type system or classification.
-
D.
hasMatch
Indicates that one entity corresponds to, aligns with, or is considered an equivalent or suitable counterpart to another entity.
-
E.
includesMatchType
Indicates that one entity’s set or collection contains an element with a specified type of match (e.g., exact, partial, or pattern-based) to another entity.
- 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_69f76e0bb6608190ad3a1880be54a17d |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a02f10505988190be5fd57566a90e0f |
completed | May 12, 2026, 9:21 a.m. |
| PD | Predicate disambiguation | batch_6a02f03a8c1481909e137e270119f7ef |
completed | May 12, 2026, 9:17 a.m. |
Created at: May 3, 2026, 4:05 p.m.