Triple
T13958465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bordeaux Métropole |
E335728
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Cenon |
E874609
|
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: Cenon | Statement: [Bordeaux Métropole, contains, Cenon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cenon Context triple: [Bordeaux Métropole, contains, Cenon]
-
A.
Cenon
chosen
Cenon is a suburban commune in southwestern France located just east of the city of Bordeaux.
-
B.
Clusone
Clusone is a historic town in northern Italy known for its medieval architecture and frescoes, located in the Lombardy region.
-
C.
Carnide
Carnide is a civil parish and residential neighborhood in northern Lisbon, Portugal, known for its mix of historic village core and modern urban developments.
-
D.
Caesonia
Caesonia is a Roman cognomen (family name) used by women of the gens Atia in ancient Rome.
-
E.
Cosentia
Cosentia is the ancient Latin name of the city now known as Cosenza in southern Italy, historically an important center of the Bruttii in Calabria.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e7a34f08190aa0d88b66154f268 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1d490048190b28cb44dd4ec46c4 |
completed | May 6, 2026, 8:17 p.m. |
Created at: April 9, 2026, 10:17 p.m.