Triple
T18481044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oberalm |
E451556
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object | Bad Vigaun |
—
|
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: Bad Vigaun | Statement: [Oberalm, hasNeighbouringMunicipality, Bad Vigaun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Vigaun Context triple: [Oberalm, hasNeighbouringMunicipality, Bad Vigaun]
-
A.
Bad Vigaun
chosen
Bad Vigaun is a small spa and health resort town in the Austrian state of Salzburg, known for its thermal baths and scenic Alpine surroundings.
-
B.
Vergongheon
Vergongheon is a commune in south-central France, located in the Haute-Loire department within the Auvergne-Rhône-Alpes region.
-
C.
Bad Laer
Bad Laer is a small spa town in Lower Saxony, Germany, known for its therapeutic mineral springs and health tourism.
-
D.
Vankarem
Vankarem is a small rural settlement located in the remote Arctic region of Chukotka in Russia.
-
E.
Bad Bibra
Bad Bibra is a small spa town in the Burgenlandkreis district of Saxony-Anhalt in central Germany, known for its rural setting and historical bathing tradition.
- 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e531d3d13c81909c52d797360b840a |
completed | April 19, 2026, 7:49 p.m. |
Created at: April 10, 2026, 11:35 a.m.