Triple
T35628437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elimination Chamber 2019 |
E1029518
|
entity |
| Predicate | womenTagChamberParticipants |
P183560
|
FINISHED |
| Object | Bayley and Sasha Banks |
—
|
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: Bayley and Sasha Banks | Statement: [Elimination Chamber 2019, womenTagChamberParticipants, Bayley and Sasha Banks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: womenTagChamberParticipants Context triple: [Elimination Chamber 2019, womenTagChamberParticipants, Bayley and Sasha Banks]
-
A.
womenRepresentationMechanism
Indicates the mechanism or process through which women’s representation or participation is ensured, structured, or facilitated in a given context.
-
B.
femaleMember
Indicates that one entity is a member of a group or organization and is identified as female.
-
C.
includesChamber
Indicates that one entity contains or encompasses a specific chamber as part of its structure or composition.
-
D.
coChamber
Indicates that two entities serve together within the same legislative or deliberative chamber.
-
E.
hadWomenOrganization
Indicates that an entity was associated with or involved in an organization focused on women or women’s issues.
- 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_69f76e07bb0c8190968ea2d836fc42c9 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a01efcc08190bba489a9099b8684 |
completed | May 3, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69f79e4d885881908a3612e2e75cf84f |
completed | May 3, 2026, 7:13 p.m. |
| PDg | Predicate description generation | batch_69f79f477c4c8190a35cb6d87b1dcbd1 |
completed | May 3, 2026, 7:17 p.m. |
Created at: May 3, 2026, 4:05 p.m.