Triple

T20495525
Position Surface form Disambiguated ID Type / Status
Subject Bludenz E502861 entity
Predicate locatedNear P294 FINISHED
Object Klostertal 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: Klostertal | Statement: [Bludenz, locatedNear, Klostertal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Klostertal
Context triple: [Bludenz, locatedNear, Klostertal]
  • A. Klostertal chosen
    Klostertal is a scenic alpine valley in the Austrian state of Vorarlberg, known for its mountain landscapes, ski areas, and access to the Arlberg region.
  • B. Löstertal
    Löstertal is a locality within the town of Wadern in the Saarland region of Germany, known for its rural character and scenic surroundings.
  • C. Deggenhausertal
    Deggenhausertal is a rural municipality in the Bodenseekreis district of Baden-Württemberg in southern Germany, known for its scenic valley landscape near Lake Constance.
  • D. Lesachtal
    Lesachtal is a remote alpine municipality in the Austrian state of Carinthia, known for its unspoiled mountain landscapes and traditional rural culture.
  • E. Kammeltal
    Kammeltal is a municipality in the Bavarian region of Swabia in southern Germany.
  • 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.