Triple
T19856206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Mortainais |
E477138
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Mortain |
—
|
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: Mortain | Statement: [Le Mortainais, namedAfter, Mortain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mortain Context triple: [Le Mortainais, namedAfter, Mortain]
-
A.
Mortain
chosen
Mortain is a town in Normandy, France, known as the focal point of a major German counteroffensive during the Battle of Normandy in World War II.
-
B.
Muriaux
Muriaux is a small municipality located in the Franches-Montagnes district of the canton of Jura in northwestern Switzerland.
-
C.
Montignez
Montignez is a small former municipality in the canton of Jura in northwestern Switzerland, near the French border.
-
D.
Morlon
Morlon is a small municipality in the canton of Fribourg in western Switzerland, situated on the shores of the artificial Lake of Gruyère.
-
E.
Morgat
Morgat is a coastal village and seaside resort on the Crozon Peninsula in Brittany, France, known for its beaches and dramatic cliffs.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6586c14fc81908d34785f1088b0a9 |
completed | April 20, 2026, 4:46 p.m. |
Created at: April 10, 2026, 1:51 p.m.