Triple
T1117498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satigny |
E11133
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object | Avully |
E33266
|
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: Avully | Statement: [Satigny, hasNeighbouringMunicipality, Avully]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avully Context triple: [Satigny, hasNeighbouringMunicipality, Avully]
-
A.
Avully
chosen
Avully is a small Swiss municipality located in the canton of Geneva, near the French border.
-
B.
Avusy
Avusy is a small rural municipality located in the canton of Geneva in southwestern Switzerland, near the French border.
-
C.
Virganskaya
Virganskaya is a Russian surname most notably borne by Irina Virganskaya, the daughter of former Soviet leader Mikhail Gorbachev.
-
D.
Usakhelauri
Usakhelauri is a rare and highly prized Georgian red wine known for its natural sweetness, aromatic complexity, and limited production in the mountainous Racha region.
-
E.
Ulladulla
Ulladulla is a coastal town in New South Wales, Australia, known for its fishing harbour, beaches, and role as a popular holiday destination.
- 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_69a493252a648190ac48f8742474a5e8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bba425a8819099116e479552332e |
completed | March 1, 2026, 10:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac53999b3c8190aff1cf84a3c16909 |
completed | March 7, 2026, 4:34 p.m. |
Created at: March 1, 2026, 7:43 p.m.