Triple
T30517122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Women’s Asayish units |
E776595
|
entity |
| Predicate | hasRecruitmentPolicy |
P4702
|
FINISHED |
| Object | women-only |
—
|
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: women-only | Statement: [Women’s Asayish units, hasRecruitmentPolicy, women-only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecruitmentPolicy Context triple: [Women’s Asayish units, hasRecruitmentPolicy, women-only]
-
A.
recruitmentPolicy
chosen
Indicates the rules, criteria, and procedures an organization follows when attracting, selecting, and hiring candidates.
-
B.
hasRecruitmentProgram
Indicates that an entity runs or participates in an organized effort to attract, select, and bring in new members, employees, or participants.
-
C.
hasVacancyPolicy
Indicates that an entity has an established policy or set of rules governing how vacancies are handled or managed.
-
D.
employmentPolicy
Indicates the rules, guidelines, or practices an organization establishes to govern employment relationships and working conditions.
-
E.
hasSocialPolicy
Indicates that an entity possesses, adopts, or is governed by a particular social policy.
- 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_69f2249b23c4819087fa85496d92f43f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a00868083b081909afc3d8d4ad56b43 |
completed | May 10, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_6a0084f5f72c8190b08afa82690e322a |
completed | May 10, 2026, 1:15 p.m. |
Created at: April 29, 2026, 8:16 p.m.