Triple
T34375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Want YOU for U.S. Army poster |
E683
|
entity |
| Predicate | depictsGender |
P1581
|
FINISHED |
| Object | male figure |
—
|
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 figure | Statement: [I Want YOU for U.S. Army poster, depictsGender, male figure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsGender Context triple: [I Want YOU for U.S. Army poster, depictsGender, male figure]
-
A.
depictsPerson
Indicates that one entity visually represents or portrays a specific person.
-
B.
depicts
chosen
Indicates that one entity visually represents, portrays, or shows another entity.
-
C.
sexOrGender
Indicates that one entity has a specified biological sex or socially constructed gender identity.
-
D.
hasNumberOfGenders
Indicates the relationship that specifies how many distinct genders are associated with or recognized for a given entity.
-
E.
hasFemaleEquivalent
Indicates that one entity serves as the female counterpart or equivalent of another entity.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a2490019948190a89bb0910c60d462 |
completed | Feb. 28, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69a24872e4e481908567850168d65015 |
completed | Feb. 28, 2026, 1:44 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.