Triple
T20528999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeanne Hébuterne (au chapeau) |
E504017
|
entity |
| Predicate | depictionAttribute |
P53700
|
FINISHED |
| Object | hat |
—
|
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: hat | Statement: [Jeanne Hébuterne (au chapeau), depictionAttribute, hat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictionAttribute Context triple: [Jeanne Hébuterne (au chapeau), depictionAttribute, hat]
-
A.
depictsAttribute
chosen
Indicates that one entity visually represents or illustrates a specific attribute or characteristic of another entity.
-
B.
depictionDetail
Indicates that one depiction provides additional detail, refinement, or a closer view of what is shown in another depiction.
-
C.
depictionType
Indicates the specific manner or style in which something is visually represented or depicted.
-
D.
depictionElement
Indicates that one entity is an element or component that appears within the visual or representational depiction of another entity.
-
E.
depictionAction
Indicates an action in which one entity visually represents, illustrates, or portrays 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_69e0b4b3a6e08190ae663701f50fab8e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a06926248190942fc9608e6b85fd |
completed | April 20, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:37 a.m.