Triple
T33468320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diocese of Clermont |
E857115
|
entity |
| Predicate | locatedInCivilRegion |
P96807
|
FINISHED |
| Object | Auvergne-Rhône-Alpes |
E9576
|
NE 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: Auvergne-Rhône-Alpes | Statement: [Diocese of Clermont, locatedInCivilRegion, Auvergne-Rhône-Alpes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInCivilRegion Context triple: [Diocese of Clermont, locatedInCivilRegion, Auvergne-Rhône-Alpes]
-
A.
locatedInTraditionalRegion
Indicates that an entity is situated within a specific traditional or historically recognized region.
-
B.
locatedInRegionalDistrict
Indicates that one entity is geographically situated within the boundaries of a specified regional district.
-
C.
regionOfCity
Indicates that a specified area or district is a constituent part or subdivision of a particular city.
-
D.
locatedInNationCapitalRegion
Indicates that an entity is situated within the capital region of a specific nation.
-
E.
locatedInStateOrRegion
chosen
Indicates that one entity is geographically situated within the boundaries of a specified state or region.
- F. None of above.
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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a36270301a08190963e13ccc9051dc2 |
completed | June 20, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:37 a.m.