Triple
T17425608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manche |
E423729
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Coutances |
—
|
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: Coutances | Statement: [Manche, hasCity, Coutances]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coutances Context triple: [Manche, hasCity, Coutances]
-
A.
Coutances
chosen
Coutances is a historic town in northwestern France known for its Gothic cathedral and role as an administrative and cultural center in the Manche department of Normandy.
-
B.
Bellême
Bellême is a historic town in northwestern France’s Normandy region, known for its medieval architecture and picturesque setting on the edge of the Perche forest.
-
C.
Nancoury
Nancoury is an alternative name for the Nancowry language, an Austroasiatic language spoken in India’s Nicobar Islands.
-
D.
Angeville
Angeville is a small commune in the Tarn-et-Garonne department in southern France.
-
E.
Bonville
Bonville is a small rural locality in New South Wales, Australia, known for its scenic countryside and proximity to the coastal city of Coffs Harbour.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e448fbfda88190be1c001d64289bf7 |
completed | April 19, 2026, 3:16 a.m. |
Created at: April 10, 2026, 5:46 a.m.