Triple
T33986083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tulle |
E871412
|
entity |
| Predicate | arrondissementSeatOf |
P115205
|
FINISHED |
| Object | Arrondissement of Tulle |
—
|
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: Arrondissement of Tulle | Statement: [Tulle, arrondissementSeatOf, Arrondissement of Tulle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arrondissementSeatOf Context triple: [Tulle, arrondissementSeatOf, Arrondissement of Tulle]
-
A.
capitalOfArrondissement
chosen
Indicates that a place serves as the administrative capital (seat) of a specified arrondissement.
-
B.
countryCapitalArrondissement
Indicates that a given arrondissement is an administrative district within the capital city of a specified country.
-
C.
capitalOfCommune
Indicates that one place serves as the administrative capital or chief town of a given commune.
-
D.
municipalitySeat
Indicates that one entity serves as the administrative center or capital (seat) of a municipality.
-
E.
hasArrondissement
Indicates a relationship where an administrative unit or locality is associated with, or belongs to, a specific arrondissement.
- 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7064e906881909c3186c646145d34 |
completed | May 3, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69f70100ec1c8190a6b97f50e88891f2 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:50 a.m.