Triple
T38021493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Denton |
E948642
|
entity |
| Predicate | schoolSubjectAssociatedWith |
P177045
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Walter Denton, schoolSubjectAssociatedWith, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: schoolSubjectAssociatedWith Context triple: [Walter Denton, schoolSubjectAssociatedWith, English]
-
A.
schoolSubject
Indicates that an entity is an academic subject taught, studied, or associated with a school or educational program.
-
B.
schoolSubjectContext
Indicates that an entity is being considered specifically in the context of a school subject or academic discipline.
-
C.
schoolSubjectRelationship
chosen
Indicates a relationship where one entity is a school subject that another entity studies, teaches, or is otherwise academically associated with.
-
D.
teachingSubject
Indicates that an entity is engaged in teaching or instructing another entity in a particular subject or field of knowledge.
-
E.
nameOfSubject
Indicates that the predicate specifies the name or label assigned to the subject 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_69f76efc10448190aff5fb566b98f952 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 3, 2026, 4:20 p.m.