Triple
T19350510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haute-Vienne |
E484003
|
entity |
| Predicate | hasNumberOfArrondissements |
P135531
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Haute-Vienne, hasNumberOfArrondissements, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfArrondissements Context triple: [Haute-Vienne, hasNumberOfArrondissements, 3]
-
A.
hasArrondissement
Indicates a relationship where an administrative unit or locality is associated with, or belongs to, a specific arrondissement.
-
B.
capitalOfArrondissement
Indicates that a place serves as the administrative capital (seat) of a specified arrondissement.
-
C.
hasNumberOfMunicipalities
Indicates the relationship that specifies how many municipalities are associated with or contained within a given administrative or geographic entity.
-
D.
hasCommune
Indicates a relationship where an entity is associated with, belongs to, or is located within a specific commune (municipal administrative unit).
-
E.
hasUrbanAgglomeration
Indicates that an entity includes, is associated with, or is characterized by a specific urban agglomeration (a densely populated urban area and its surrounding zones).
- 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_69d8e8d244f8819080eb1f3491300db2 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e6190381c081909c747a22422fb02c |
completed | April 20, 2026, 12:16 p.m. |
| PD | Predicate disambiguation | batch_69e4dd12303c8190a2027c062b2dff40 |
completed | April 19, 2026, 1:48 p.m. |
| PDg | Predicate description generation | batch_69e4df51ac6c819091ce72b07790ffa6 |
completed | April 19, 2026, 1:57 p.m. |
Created at: April 10, 2026, 1:34 p.m.