Triple
T14850447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashes |
E349210
|
entity |
| Predicate | hasFemaleFigurePose |
P15582
|
FINISHED |
| Object | woman clutching her head |
—
|
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: woman clutching her head | Statement: [Ashes, hasFemaleFigurePose, woman clutching her head]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFemaleFigurePose Context triple: [Ashes, hasFemaleFigurePose, woman clutching her head]
-
A.
showsPose
chosen
Indicates that one entity displays or presents a particular pose or bodily posture of another entity.
-
B.
hasFemaleCharacter
Indicates that an entity includes or features at least one female character.
-
C.
femaleHas
Indicates that a specified entity is female or possesses a female gender attribute in relation to another entity or context.
-
D.
hasFemaleEquivalent
Indicates that one entity serves as the female counterpart or equivalent of another entity.
-
E.
femaleFeature
Indicates that the subject possesses a characteristic or attribute that is typically associated with females.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded43eee188190bf24dc475b3abe28 |
completed | April 14, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69de8c1798c08190b433e9ad21e41a42 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:54 a.m.