Triple
T22601490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Women’s Mid-Amateur |
E574831
|
entity |
| Predicate | professionalParticipationAllowed |
P31379
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [U.S. Women’s Mid-Amateur, professionalParticipationAllowed, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalParticipationAllowed Context triple: [U.S. Women’s Mid-Amateur, professionalParticipationAllowed, false]
-
A.
professionalStatusRestriction
chosen
Indicates a limitation or condition placed on someone’s professional role, eligibility, or activities.
-
B.
professionalMembership
Indicates that an entity holds membership or affiliation in a professional organization, association, or body.
-
C.
hasProfessionalStatusRequirement
Indicates that something is subject to a condition specifying a particular professional status that must be held or met.
-
D.
hasProfessionalStatus
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
E.
hasProfessionalSection
Indicates that an entity includes or is associated with a designated professional section, division, or category within its structure or content.
- 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_69e245bc11308190b69d794d5d1e0bb6 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1626db69481908ec9f9c7d320d3cb |
completed | April 29, 2026, 1:44 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 2:50 p.m.