Triple
T28273458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Body Count |
E712917
|
entity |
| Predicate | hasFemalePerspective |
P109486
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Body Count, hasFemalePerspective, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFemalePerspective Context triple: [Body Count, hasFemalePerspective, true]
-
A.
hasFemaleSpeaker
Indicates that the associated content, event, or communication is spoken or narrated by a female individual.
-
B.
hasGenderFocus
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
-
C.
femaleHas
Indicates that a specified entity is female or possesses a female gender attribute in relation to another entity or context.
-
D.
hasGenderRepresentation
chosen
Indicates that something includes, reflects, or portrays one or more genders within its content, structure, or composition.
-
E.
attitudeTowardWomen
Indicates the nature or quality of a subject’s views, feelings, or behavioral disposition toward women.
- 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_69efb52275788190ae5181ccebef18ce |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6a8df16a88190a23820e64a3b1f92 |
completed | May 3, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 27, 2026, 11:19 p.m.