Triple
T13842145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carnetin |
E332684
|
entity |
| Predicate | isInMetropolitanFrance |
P50406
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Carnetin, isInMetropolitanFrance, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInMetropolitanFrance Context triple: [Carnetin, isInMetropolitanFrance, yes]
-
A.
locatedInMetropolitanFrance
chosen
Indicates that the subject is geographically situated within the territory of metropolitan (continental) France.
-
B.
hasFrenchSector
Indicates that an entity includes, controls, or is associated with a sector or area designated as French.
-
C.
isLocatedInMetropolitanCity
Indicates that an entity is situated within a metropolitan city area.
-
D.
isMetropolitanFor
Indicates that one entity serves as the primary metropolitan center or urban hub for another entity (such as a region, area, or service).
-
E.
isLocatedOnFrenchRiviera
Indicates that something is situated in a place that is part of the French Riviera coastal region.
- 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02afce788190a74dce4e6a3569fa |
completed | April 14, 2026, 9:02 a.m. |
| PD | Predicate disambiguation | batch_69dbc86668e08190ba9135d1c3f38d35 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:13 p.m.