Triple
T38326059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austrian universities |
E1036786
|
entity |
| Predicate | belongToArea |
P86016
|
FINISHED |
| Object | European Higher Education Area |
—
|
NE NERFINISHED |
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: European Higher Education Area | Statement: [Austrian universities, belongToArea, European Higher Education Area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongToArea Context triple: [Austrian universities, belongToArea, European Higher Education Area]
-
A.
hasAreaName
Indicates that an entity is associated with a specific named geographic or administrative area.
-
B.
believedToBelongTo
Indicates that something is thought or assumed, but not definitively known, to be owned by or part of a particular entity.
-
C.
regionOfAssociation
chosen
Indicates a broader geographic or spatial area with which an entity is functionally, contextually, or organizationally associated.
-
D.
assignedToArea
Indicates that something has been allocated or designated to a specific area or region.
-
E.
relatedVenueArea
Indicates that a venue is associated with or located within a particular geographic or spatial area.
- 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_69f76e1c16fc8190bde982289dd5106b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a0058c341ac8190825067dc25158839 |
completed | May 10, 2026, 10:06 a.m. |
| PD | Predicate disambiguation | batch_6a005857249c81908b27587b84d84dbb |
completed | May 10, 2026, 10:05 a.m. |
Created at: May 3, 2026, 4:30 p.m.