Triple
T5701444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Winnower |
E125671
|
entity |
| Predicate | hasHumanFigure |
P61746
|
FINISHED |
| Object | male peasant |
—
|
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: male peasant | Statement: [The Winnower, hasHumanFigure, male peasant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHumanFigure Context triple: [The Winnower, hasHumanFigure, male peasant]
-
A.
containsHumanFigures
chosen
Indicates that the subject includes one or more human figures within its content or composition.
-
B.
hasAnimatedFigures
Indicates that something contains or features figures that are animated or capable of motion.
-
C.
numberOfFiguresDepicted
Indicates the total count of distinct figures shown within a given depiction or representation.
-
D.
hasIconographicFigure
Indicates that one entity includes, depicts, or is associated with a particular iconographic figure in its visual or symbolic representation.
-
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_69c0082c96988190b3a6a201edce472a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024540afc8190aee3760f71ea39c2 |
completed | March 22, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.