Triple
T5701429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Winnower |
E125671
|
entity |
| Predicate | depictsNumberOfHumanFigures |
P6685
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [The Winnower, depictsNumberOfHumanFigures, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsNumberOfHumanFigures Context triple: [The Winnower, depictsNumberOfHumanFigures, 1]
-
A.
numberOfFiguresDepicted
chosen
Indicates the total count of distinct figures shown within a given depiction or representation.
-
B.
containsHumanFigures
Indicates that the subject includes one or more human figures within its content or composition.
-
C.
depictsPerson
Indicates that one entity visually represents or portrays a specific person.
-
D.
depictedAbove
Indicates that one entity is visually represented in an image, illustration, or diagram that is positioned above another referenced element in a layout or document.
-
E.
depictedSubject
Indicates that one entity visually represents or portrays another entity as its subject in an image or depiction.
- 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.