Triple
T17311222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | mountainRevels |
E420297
|
entity |
| Predicate | coreParticipantsGender |
P113101
|
FINISHED |
| Object | primarily 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: primarily female | Statement: [mountainRevels, coreParticipantsGender, primarily female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coreParticipantsGender Context triple: [mountainRevels, coreParticipantsGender, primarily female]
-
A.
genderOfMembers
chosen
Indicates the gender or genders associated with the members of a group or organization.
-
B.
genderOfResidents
Indicates the gender identity or classification associated with the residents of a particular place or group.
-
C.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
-
D.
featuredGender
Indicates that a particular gender is highlighted, emphasized, or given primary focus in a given context or presentation.
-
E.
hasGenderRepresentation
Indicates that something includes, reflects, or portrays one or more genders within its content, structure, or composition.
- 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4399837b08190b7cf74201b3cb013 |
completed | April 19, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69e3b01b9d1c8190a406dd941c9b11a1 |
completed | April 18, 2026, 4:23 p.m. |
Created at: April 10, 2026, 5:43 a.m.