Triple
T23922705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novecento Italiano artists |
E602261
|
entity |
| Predicate | preferredSubjectMatter |
P450
|
FINISHED |
| Object | history 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: history painting | Statement: [Novecento Italiano artists, preferredSubjectMatter, history painting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preferredSubjectMatter Context triple: [Novecento Italiano artists, preferredSubjectMatter, history painting]
-
A.
primarySubjectArea
Indicates the main academic or topical field to which something (such as a work, course, or resource) is most centrally related.
-
B.
subjectMatter
chosen
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
C.
primaryInterest
Indicates that one entity is the main or most significant focus of attention, concern, or engagement for another entity.
-
D.
subjectChoice
Indicates that an entity makes, has, or is associated with a particular choice or selection among alternatives.
-
E.
subjectSpecialization
Indicates that one subject focuses on, or has expertise in, a particular field, topic, or area of knowledge.
- 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_69e2953b928c819095395fa87baca583 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cf19e34481909909bda3f52cabb3 |
completed | April 29, 2026, 9:27 a.m. |
| PD | Predicate disambiguation | batch_69f16151ebdc819086e9e1d7cc1f4f3c |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:41 p.m.