Triple
T21569614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tinchebray |
E532250
|
entity |
| Predicate | mergedInto |
P77
|
FINISHED |
| Object | Tinchebray-Bocage |
—
|
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: Tinchebray-Bocage | Statement: [Tinchebray, mergedInto, Tinchebray-Bocage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tinchebray-Bocage Context triple: [Tinchebray, mergedInto, Tinchebray-Bocage]
-
A.
Tinchebray-Bocage
chosen
Tinchebray-Bocage is a commune in the Orne department of northwestern France, formed by the merger of several former communes including Tinchebray.
-
B.
Mortain-Bocage
Mortain-Bocage is a commune in the Manche department of northwestern France, known for its historic town of Mortain and its scenic bocage landscape.
-
C.
Nancoury
Nancoury is an alternative name for the Nancowry language, an Austroasiatic language spoken in India’s Nicobar Islands.
-
D.
Tinchebrayens
Tinchebrayens are the inhabitants or natives of Tinchebray, a commune in the Orne department of northwestern France.
-
E.
Coye-la-Forêt
Coye-la-Forêt is a small commune in the Oise department of northern France, known for its forested surroundings and residential character near the Chantilly area.
- 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_69e0c460db088190828c64206a450273 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eee9cb9718819094fc95b25df68bd1 |
completed | April 27, 2026, 4:44 a.m. |
Created at: April 16, 2026, 6:30 p.m.