Triple
T10864489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attalens |
E256491
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object | Remaufens |
E806448
|
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: Remaufens | Statement: [Attalens, hasNeighboringMunicipality, Remaufens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Remaufens Context triple: [Attalens, hasNeighboringMunicipality, Remaufens]
-
A.
Remaufens
chosen
Remaufens is a small municipality in the canton of Fribourg in western Switzerland.
-
B.
Reureu
Reureu is a village settlement on the island of Aitutaki in the Cook Islands.
-
C.
Reitoca
Reitoca is a municipality in southern Honduras known for its rural character and location within the Francisco Morazán Department.
-
D.
Resegone
Resegone is a distinctive serrated mountain massif in the Bergamo Alps of northern Italy, overlooking the city of Lecco and famed for its saw-like ridgeline.
-
E.
Rehe
Rehe was a historical province in northeastern China that served as a strategic frontier region between the Great Wall and Manchuria.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7516b2f148190adbacd35fc8c2056 |
completed | April 9, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7d5359c8190b46a6b817938eb67 |
completed | April 15, 2026, 8:40 p.m. |
Created at: April 8, 2026, 9:20 p.m.