Triple
T38431098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fist City |
E903801
|
entity |
| Predicate | portraysImageOf |
P97263
|
FINISHED |
| Object | strong working-class woman |
—
|
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: strong working-class woman | Statement: [Fist City, portraysImageOf, strong working-class woman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysImageOf Context triple: [Fist City, portraysImageOf, strong working-class woman]
-
A.
evokesImageOf
Indicates that one entity triggers or brings to mind a mental image or visual representation of another entity.
-
B.
imageDepictedIn
Indicates that a particular image is shown, represented, or included within another resource or context.
-
C.
imageOf
chosen
Indicates that one entity is a visual representation or depiction of another entity.
-
D.
portraysPersonAs
Indicates that one entity represents, depicts, or characterizes another person in a particular way or role.
-
E.
portraitOn
Indicates that one entity is depicted as a portrait on the surface or medium 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_69f76e6a2024819081aa04f4932f89d2 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ffcf46fd688190907fd1ceb499a8d1 |
completed | May 10, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69ffccde2a8c81908e055e74077dbd19 |
completed | May 10, 2026, 12:10 a.m. |
Created at: May 3, 2026, 4:31 p.m.