Triple
T19015172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County of Montfort |
E465328
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Montfort-l’Amaury |
—
|
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: Montfort-l’Amaury | Statement: [County of Montfort, namedAfter, Montfort-l’Amaury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montfort-l’Amaury Context triple: [County of Montfort, namedAfter, Montfort-l’Amaury]
-
A.
Montfort-l'Amaury–Méré
Montfort-l'Amaury–Méré is a railway station in north-central France that connects the towns of Montfort-l'Amaury and Méré to the Paris suburban rail network.
-
B.
Montfort-sur-Meu
Montfort-sur-Meu is a small historic town in the Ille-et-Vilaine department of Brittany in northwestern France.
-
C.
Montfort
Montfort is a masculine given name of French origin, historically associated with nobility and figures such as colonial administrator Montfort Browne.
-
D.
Montfort-l'Amaury, France
chosen
Montfort-l'Amaury is a historic commune in north-central France known as the medieval seat of the Montfort family and for its well-preserved old town and castle ruins.
-
E.
Angeville
Angeville is a small commune in the Tarn-et-Garonne department in southern France.
- 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_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6d9f2a081908c0e923809da88e2 |
completed | April 20, 2026, 7:33 a.m. |
Created at: April 10, 2026, 12:02 p.m.