Triple
T8043428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seated Harlequin |
E187488
|
entity |
| Predicate | hasSubjectMatterCategory |
P450
|
FINISHED |
| Object | figure 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: figure painting | Statement: [Seated Harlequin, hasSubjectMatterCategory, figure painting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectMatterCategory Context triple: [Seated Harlequin, hasSubjectMatterCategory, figure painting]
-
A.
subjectMatterScope
Indicates the thematic or topical domain that an action, statement, or resource pertains to or falls within.
-
B.
subjectMatter
chosen
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
C.
hasInstitutionalCategory
Indicates that an entity is classified under a specific institutional type or category within an organizational or institutional framework.
-
D.
hasBibliographicCategory
Indicates that an entity is associated with a specific bibliographic classification or category within a cataloging or documentation system.
-
E.
hasPrimarySubject
Indicates that an entity is the main or principal subject associated with another entity or resource.
- 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_69ca82b00cb48190b59a300f70e97bd7 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3f4b5e0c819092949af0f995b850 |
completed | March 31, 2026, 3:28 a.m. |
| PD | Predicate disambiguation | batch_69cb049688208190b32088bd2c5930bc |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:23 p.m.