Triple
T28579946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portraiture (Oxford History of Art) |
E723343
|
entity |
| Predicate | coversForm |
P175237
|
FINISHED |
| Object | painting |
—
|
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: painting | Statement: [Portraiture (Oxford History of Art), coversForm, painting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coversForm Context triple: [Portraiture (Oxford History of Art), coversForm, painting]
-
A.
coversFrom
Indicates that one entity provides protection, concealment, or shelter for another entity against something originating from a specified source or direction.
-
B.
coversField
Indicates that one entity extends over, protects, or occupies the surface or area of a field associated with another entity.
-
C.
cover
Indicates that one entity extends over, conceals, protects, or provides a surface or layer for another entity.
-
D.
coversTo
Indicates that one entity extends its coverage or protective scope to include another entity.
-
E.
coverVersionBy
Indicates that one creative work is a cover version performed or produced by a particular artist or 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_69f01d7e97708190ae9e77ee66a68abd |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6cee547108190ad3bc84297d8f516 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1188708190b8f0f56e595e6057 |
completed | May 3, 2026, 4:16 a.m. |
| PDg | Predicate description generation | batch_69f6cee3604c81908a07eade2f39064e |
completed | May 3, 2026, 4:28 a.m. |
Created at: April 28, 2026, 4:14 a.m.