Triple

T20886783
Position Surface form Disambiguated ID Type / Status
Subject Grob Aircraft airfield E514301 entity
Predicate near P350 FINISHED
Object Bad Wörishofen 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 Wörishofen | Statement: [Grob Aircraft airfield, near, Bad Wörishofen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bad Wörishofen
Context triple: [Grob Aircraft airfield, near, Bad Wörishofen]
  • A. Bad Wörishofen chosen
    Bad Wörishofen is a spa town in Bavaria, Germany, renowned as the birthplace of Sebastian Kneipp’s hydrotherapy and wellness treatments.
  • B. Bad Schönau
    Bad Schönau is a small spa town in Lower Austria known for its therapeutic mineral springs and tranquil rural setting.
  • C. Bad Schussenried
    Bad Schussenried is a spa town in southern Germany known for its historic monastery complex and scenic location in Upper Swabia.
  • D. Bad Füssing
    Bad Füssing is a German spa town in Bavaria renowned for its thermal baths and health tourism.
  • E. Bad Wiessee
    Bad Wiessee is a Bavarian spa town in southern Germany, known for its therapeutic iodine-sulfur springs and scenic location on the shores of Lake Tegernsee.
  • 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_69e0b4f733f081908a401c0b7beb0b9f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6d058d4dc81908398f8c75e30dc77 completed April 21, 2026, 1:18 a.m.
Created at: April 16, 2026, 12:46 p.m.