Triple
T3007366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manche |
E81934
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Coutances |
E319547
|
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: Coutances | Statement: [Manche, containsCity, Coutances]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coutances Context triple: [Manche, containsCity, 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.
Brouage
Brouage is a historic fortified coastal village in southwestern France, known as the birthplace of explorer Samuel de Champlain and once an important salt-trading port.
-
C.
Lisieux
Lisieux is a town and commune in the Calvados department of Normandy in northwestern France, known as a major Catholic pilgrimage site associated with Saint Thérèse of Lisieux.
-
D.
Langeac
Langeac is a small commune in south-central France, situated in the Haute-Loire department within the Auvergne-Rhône-Alpes region.
-
E.
Brienne-le-Château
Brienne-le-Château is a commune in northeastern France best known as the town where Napoleon Bonaparte attended military school in his youth.
- 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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a4a12508190a48ae1c86233d25e |
completed | March 8, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1dea6b460819087d7186efc901ef2 |
completed | March 11, 2026, 9:29 p.m. |
Created at: March 8, 2026, 3 p.m.