Triple
T898755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jewish studies |
E19400
|
entity |
| Predicate | academicApproach |
P20107
|
FINISHED |
| Object | historical |
—
|
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: historical | Statement: [Jewish studies, academicApproach, historical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicApproach Context triple: [Jewish studies, academicApproach, historical]
-
A.
academicEmphasis
Indicates a focus or concentration of study or specialization within an academic program or curriculum.
-
B.
academicFocus
Indicates the primary field of study, discipline, or subject area that an entity concentrates on academically.
-
C.
academicContext
Indicates the educational or scholarly setting, framework, or circumstances within which an activity, relationship, or piece of information takes place.
-
D.
academicType
Indicates the specific academic category or classification associated with an entity (such as a work, program, or role).
-
E.
researchApproach
Indicates the methodological strategy or set of methods used to conduct and structure a research activity or investigation.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad4162848190aa2787b2fa3e6575 |
completed | March 1, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69a4aa9635608190a297e2067b8dcee2 |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab4ae71081909e5286c90cb6e394 |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:39 p.m.