Triple
T19826601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Domont |
E476340
|
entity |
| Predicate | containsCommune |
P15149
|
FINISHED |
| Object | Montlignon |
—
|
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: Montlignon | Statement: [canton of Domont, containsCommune, Montlignon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montlignon Context triple: [canton of Domont, containsCommune, Montlignon]
-
A.
Montlignon
chosen
Montlignon is a small commune in the Val-d'Oise department in the Île-de-France region of northern France.
-
B.
Monpezat
Monpezat is a French noble family name associated with Prince Henrik of Denmark and his descendants.
-
C.
Jaunay-Marigny
Jaunay-Marigny is a commune in western France’s Vienne department, notable for hosting the popular Futuroscope theme park.
-
D.
Saignon
Saignon is a picturesque hilltop village in southeastern France’s Vaucluse department, known for its medieval architecture and panoramic views over the Luberon valley.
-
E.
Morieux
Morieux is a coastal commune in the Côtes-d'Armor department of Brittany in northwestern France, known for its scenic shoreline along the English Channel.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656cb20788190b9deac6b8af6a55d |
completed | April 20, 2026, 4:39 p.m. |
Created at: April 10, 2026, 1:50 p.m.