Triple
T1664214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Lecture |
E35973
|
entity |
| Predicate | depictionFocus |
P30524
|
FINISHED |
| Object | female 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: female figure | Statement: [La Lecture, depictionFocus, female figure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictionFocus Context triple: [La Lecture, depictionFocus, female figure]
-
A.
depictionDetail
Indicates that one depiction provides additional detail, refinement, or a closer view of what is shown in another depiction.
-
B.
depictionType
Indicates the specific manner or style in which something is visually represented or depicted.
-
C.
depictionPurpose
Indicates that one entity is depicted specifically for the purpose or function it serves in relation to another entity.
-
D.
depictionContext
Indicates the situational or environmental setting in which something is depicted or represented.
-
E.
depicts
Indicates that one entity visually represents, portrays, or shows another entity.
- F. None of above. chosen
Provenance (4 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_69a88606aa808190aa0b421b4271f220 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa994f92b0819084ee2f6a672334b9 |
completed | March 6, 2026, 9:07 a.m. |
| PD | Predicate disambiguation | batch_69a907d2475c8190b7ec7dccd3335eb1 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a94192abc0819092fc00fef9d53bcb |
completed | March 5, 2026, 8:40 a.m. |
Created at: March 4, 2026, 7:29 p.m.