Triple
T2175526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Université Grenoble Alpes campus in Valence |
E48517
|
entity |
| Predicate | locatedInPartOfFrance |
P17086
|
FINISHED |
| Object | southeastern France |
—
|
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: southeastern France | Statement: [Université Grenoble Alpes campus in Valence, locatedInPartOfFrance, southeastern France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInPartOfFrance Context triple: [Université Grenoble Alpes campus in Valence, locatedInPartOfFrance, southeastern France]
-
A.
hasFrenchSector
Indicates that an entity includes, controls, or is associated with a sector or area designated as French.
-
B.
statusInFrance
Indicates the legal, social, or official standing or condition that an entity has within the jurisdiction of France.
-
C.
locatedOnTerritoryOf
chosen
Indicates that one entity is situated within or on the land area governed or owned by another entity.
-
D.
strengthFrance
Indicates a relationship where a level, measure, or attribute of strength is associated specifically with France.
-
E.
isLocatedOn
Indicates that one entity exists at or is situated upon the surface or area of another 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc4358fc88190a6f556c2de9fef8c |
completed | March 7, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69abbda0ec948190be88c1243d81a423 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.