Triple
T36366186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lumières de Noël de Montbéliard |
E895630
|
entity |
| Predicate | typeDeLieu |
P77125
|
FINISHED |
| Object | centre-ville |
—
|
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: centre-ville | Statement: [Lumières de Noël de Montbéliard, typeDeLieu, centre-ville]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeDeLieu Context triple: [Lumières de Noël de Montbéliard, typeDeLieu, centre-ville]
-
A.
spaceType
chosen
Indicates the category or kind of physical or conceptual space associated with an entity.
-
B.
emplacementType
Indicates the specific manner or configuration in which something is positioned, installed, or set in place relative to its surroundings.
-
C.
typeOfLandmark
Indicates the specific category or kind of landmark that an entity belongs to (e.g., monument, natural feature, building).
-
D.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
E.
arealTypology
Indicates a typological relationship based on geographic or areal distribution, showing how linguistic features are shared or patterned across regions.
- 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_69f76e5115588190ad8738860b7bc68b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb3ff1b08190802b1063d55d3923 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a611a081908dd6aec1df3f4d7f |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:10 p.m.