Triple
T20495526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bludenz |
E502861
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Montafon |
—
|
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: Montafon | Statement: [Bludenz, locatedNear, Montafon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montafon Context triple: [Bludenz, locatedNear, Montafon]
-
A.
Montafon
chosen
Montafon is a scenic alpine valley in the Austrian state of Vorarlberg, known for its mountain landscapes, skiing, and hiking opportunities.
-
B.
Arnegg
Arnegg is a village and district of the municipality of Blaustein in the Alb-Donau district of Baden-Württemberg, Germany.
-
C.
Schruns
Schruns is a small alpine town and popular ski resort in the Montafon valley of Vorarlberg, western Austria.
-
D.
Obergurgl
Obergurgl is a high-altitude Austrian alpine village and ski resort in the Ötztal Alps, known for its reliable snow and extensive winter sports facilities.
-
E.
Neustift
Neustift is a district of the Bavarian city of Passau, Germany, known primarily as a residential area on the outskirts of the historic center.
- 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cbd2dfc81908204f7bfa8a763b6 |
completed | April 20, 2026, 9:38 p.m. |
Created at: April 16, 2026, 11:35 a.m.