Triple
T3007359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manche |
E81934
|
entity |
| Predicate | bordersDepartment |
P224
|
FINISHED |
| Object | Orne |
E123324
|
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: Orne | Statement: [Manche, bordersDepartment, Orne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orne Context triple: [Manche, bordersDepartment, Orne]
-
A.
Orne
chosen
Orne is a rural department in northwestern France known for its pastoral landscapes, horse breeding, and historic towns such as Alençon.
-
B.
Olne
Olne is a small municipality in the province of Liège in Wallonia, eastern Belgium, known for its rural character and traditional village charm.
-
C.
Avre
The Avre is a river in northern France that serves as a tributary of the Eure, flowing through the Normandy and Centre-Val de Loire regions.
-
D.
Nahe
Nahe is a renowned German wine region, particularly celebrated for producing high-quality Riesling wines with diverse styles due to its varied soils and microclimates.
-
E.
Methil
Methil is a coastal town in eastern Scotland that forms part of the Levenmouth area on the Firth of Forth.
- 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_69b12e5b35e48190a9319a545d041ccc |
completed | March 11, 2026, 8:56 a.m. |
Created at: March 8, 2026, 3 p.m.