Triple
T26149498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tenebrism |
E659774
|
entity |
| Predicate | commonSubjectMatter |
P450
|
FINISHED |
| Object | biblical narratives |
—
|
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: biblical narratives | Statement: [Tenebrism, commonSubjectMatter, biblical narratives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonSubjectMatter Context triple: [Tenebrism, commonSubjectMatter, biblical narratives]
-
A.
commonCourse
Indicates that two or more entities share at least one course in common.
-
B.
commonEducation
Indicates that two or more entities share at least one educational experience in common, such as attending the same school, program, or course.
-
C.
subjectMatter
chosen
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
D.
schoolSubject
Indicates that an entity is an academic subject taught, studied, or associated with a school or educational program.
-
E.
primarySubjectArea
Indicates the main academic or topical field to which something (such as a work, course, or resource) is most centrally related.
- 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_69ee5bc496a88190af7deb7ab5e081de |
completed | April 26, 2026, 6:39 p.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a5fd8481909433e923c5e24e55 |
completed | May 3, 2026, 2:32 a.m. |
Created at: April 26, 2026, 8:24 p.m.