Triple
T18277962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chéserex |
E437786
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object | Grens |
—
|
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: Grens | Statement: [Chéserex, hasNeighboringMunicipality, Grens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grens Context triple: [Chéserex, hasNeighboringMunicipality, Grens]
-
A.
Grens
chosen
Grens is a small municipality in the canton of Vaud in western Switzerland, situated within the Nyon District near Lake Geneva.
-
B.
Grenz
Grenz is a surname most notably associated with Stanley Grenz, a prominent late 20th-century evangelical theologian and author.
-
C.
Hranice
Hranice is a town in the Czech Republic located near the Oder Mountains, known for its historical architecture and proximity to natural landscapes.
-
D.
Riksgränsen
Riksgränsen is a remote ski resort village in northern Sweden near the Norwegian border, renowned for its late-season skiing under the midnight sun.
-
E.
Fronteira
Fronteira is a small Portuguese municipality in the Alentejo region, known for its rural landscape and historical heritage.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50053cc808190b46a3ec9d96936fe |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 10:34 a.m.