Triple

T12749587
Position Surface form Disambiguated ID Type / Status
Subject Rostock–Laage Airport E304694 entity
Predicate locatedIn P40 FINISHED
Object Laage E487011 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: Laage | Statement: [Rostock–Laage Airport, locatedIn, Laage]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laage
Context triple: [Rostock–Laage Airport, locatedIn, Laage]
  • A. Laage chosen
    Laage is a small town in the Rostock district of Mecklenburg-Vorpommern in northern Germany, known for its proximity to Rostock–Laage Airport.
  • B. Dalhem
    Dalhem is a historic municipality in the province of Liège in eastern Belgium, known for its medieval heritage and rural character.
  • C. Raalte
    Raalte is a town and municipality in the Dutch province of Overijssel, known for its agricultural surroundings and regional festivals.
  • D. Soest
    Soest is a Dutch town and municipality in the central Netherlands known for its green surroundings and proximity to the Utrechtse Heuvelrug.
  • E. Soest
    Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
  • 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96bd75f508190aaae0969f33d1523 completed April 10, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c964c508190b4d6a094b388280b completed May 2, 2026, 10:37 p.m.
Created at: April 9, 2026, 5:27 p.m.