Triple
T25560986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ima Keithel |
E640711
|
entity |
| Predicate | genderRestrictionForVendors |
P15554
|
FINISHED |
| Object | female |
—
|
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: female | Statement: [Ima Keithel, genderRestrictionForVendors, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderRestrictionForVendors Context triple: [Ima Keithel, genderRestrictionForVendors, female]
-
A.
hasGenderRequirement
chosen
Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
-
B.
demographicRestriction
Indicates that participation, access, or applicability is limited or conditioned based on specific demographic characteristics (such as age, gender, ethnicity, or similar attributes).
-
C.
eligibleVendors
Indicates that certain vendors meet the required criteria or conditions to be considered eligible for a specified purpose or process.
-
D.
sponsoredGender
Indicates that one entity provides financial or material sponsorship specifically related to the gender of another entity.
-
E.
hasGenderNeutralEligibility
Indicates that an entity is eligible or applicable in a way that does not depend on or specify a particular gender.
- 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_69e75dc1beb08190bac7d76b8d6e7bc4 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f8f8f1488190975d56d6dfad3d25 |
completed | May 2, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69f4a0f7c6008190ae8cee3e71e19b94 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 21, 2026, 3:46 p.m.