Triple
T33777833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bomet County |
E865568
|
entity |
| Predicate | hasWomanRepresentative |
P192
|
FINISHED |
| Object | Linet Chepkorir |
—
|
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: Linet Chepkorir | Statement: [Bomet County, hasWomanRepresentative, Linet Chepkorir]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWomanRepresentative Context triple: [Bomet County, hasWomanRepresentative, Linet Chepkorir]
-
A.
hasFemaleLeader
Indicates that the subject entity is led or governed by a woman in a primary leadership role.
-
B.
womenRepresentationMechanism
Indicates the mechanism or process through which women’s representation or participation is ensured, structured, or facilitated in a given context.
-
C.
hasRepresentativeBody
Indicates that an entity is associated with or governed by a specific representative body that acts or decides on its behalf.
-
D.
hasElectoralRepresentation
chosen
Indicates that one entity is represented in an electoral body or decision-making institution by another entity (such as a representative, party, or delegation).
-
E.
roleInMissRepresentation
Indicates that an entity has a specific role or involvement in the documentary film "Miss Representation."
- 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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fdee770af48190aca2670db50f8b49 |
completed | May 8, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69fdecec98a08190a357d816dc2a6dbe |
completed | May 8, 2026, 2:02 p.m. |
Created at: May 1, 2026, 1:45 a.m.