Triple
T1153012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Open University in Scotland |
E23719
|
entity |
| Predicate | hasStudyModel |
P25352
|
FINISHED |
| Object | modular study |
—
|
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: modular study | Statement: [Open University in Scotland, hasStudyModel, modular study]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudyModel Context triple: [Open University in Scotland, hasStudyModel, modular study]
-
A.
hasCaseStudy
Indicates that one entity is documented, illustrated, or analyzed by a specific case study associated with it.
-
B.
hasModelledFor
Indicates that one entity has served as a model for another entity, typically in a professional or representational context such as art, photography, or fashion.
-
C.
hasResearchStatus
Indicates that an entity holds a particular stage or condition within a research process, such as planned, in progress, completed, or published.
-
D.
isStudiedIn
Indicates that a subject (such as a topic, field, or phenomenon) is examined, researched, or learned about within a particular context, environment, or discipline.
-
E.
hasLanguageOfStudy
Indicates that an entity studies or is engaged in learning a particular language.
- 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc8d2dd8819081c779d408c2651d |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb50d19c81908a98dbbb04a8906f |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bc47fce48190825d3a877251f789 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:44 p.m.