Triple
T65436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Theology, University of Göttingen |
E1302
|
entity |
| Predicate | fieldOfResearch |
P934
|
FINISHED |
| Object | Old Testament studies |
—
|
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: Old Testament studies | Statement: [Faculty of Theology, University of Göttingen, fieldOfResearch, Old Testament studies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldOfResearch Context triple: [Faculty of Theology, University of Göttingen, fieldOfResearch, Old Testament studies]
-
A.
hasResearchArea
chosen
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
B.
researchClassification
Indicates that an entity is assigned a specific category or type within a research-related classification scheme.
-
C.
academicFocus
Indicates the primary field of study, discipline, or subject area that an entity concentrates on academically.
-
D.
researchStrength
Indicates the degree to which an entity possesses strong capabilities, performance, or impact in conducting research.
-
E.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a2516eda54819090f5c14384d4eab1 |
completed | Feb. 28, 2026, 2:22 a.m. |
| PD | Predicate disambiguation | batch_69a24ea5c140819080409a968c8d2ce8 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.