Triple

T20961093
Position Surface form Disambiguated ID Type / Status
Subject Eder E516244 entity
Predicate passesNear P416 FINISHED
Object Fritzlar 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: Fritzlar | Statement: [Eder, passesNear, Fritzlar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fritzlar
Context triple: [Eder, passesNear, Fritzlar]
  • A. Fritzlar chosen
    Fritzlar is a historic town in northern Hesse, Germany, known for its well-preserved medieval old town and its significance in early German Christian history.
  • B. Filderstadt
    Filderstadt is a town in the German state of Baden-Württemberg, situated just south of Stuttgart and known for its proximity to Stuttgart Airport and role as a regional transport hub.
  • C. Bruchsal
    Bruchsal is a town in the state of Baden-Württemberg in southwestern Germany, known for its baroque palace and asparagus cultivation.
  • D. Gevelsberg
    Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
  • E. Wetzlar
    Wetzlar is a historic German city in the state of Hesse, known for its medieval old town and its long tradition in optics and precision engineering.
  • 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_69e0b4fde6c48190af1398e7e734629e completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6fb6f134081908b1ed48ce708f3d5 completed April 21, 2026, 4:22 a.m.
Created at: April 16, 2026, 1:31 p.m.