Triple
T14850448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashes |
E349210
|
entity |
| Predicate | hasMaleFigurePose |
P15582
|
FINISHED |
| Object | man turned away, slumped |
—
|
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: man turned away, slumped | Statement: [Ashes, hasMaleFigurePose, man turned away, slumped]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaleFigurePose Context triple: [Ashes, hasMaleFigurePose, man turned away, slumped]
-
A.
showsPose
chosen
Indicates that one entity displays or presents a particular pose or bodily posture of another entity.
-
B.
containsHumanFigures
Indicates that the subject includes one or more human figures within its content or composition.
-
C.
isMaleCharacter
Indicates that the referenced character is identified as male.
-
D.
trainedFigure
Indicates that one entity has been trained, coached, or otherwise prepared by another entity.
-
E.
publicFigure
Indicates that an entity is widely recognized by the public and holds a prominent or influential role in society, such as in politics, entertainment, or media.
- 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.