Triple

T21195992
Position Surface form Disambiguated ID Type / Status
Subject Löhne–Rheine railway E522326 entity
Predicate connects P390 FINISHED
Object Löhne 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: Löhne | Statement: [Löhne–Rheine railway, connects, Löhne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Löhne
Context triple: [Löhne–Rheine railway, connects, Löhne]
  • A. Löhne chosen
    Löhne is a town in the district of Herford in North Rhine-Westphalia, Germany, known historically as part of the former County of Ravensberg.
  • B. Löhne-Ort
    Löhne-Ort is a district within the town of Löhne in North Rhine-Westphalia, Germany, characterized by its residential areas and local amenities.
  • C. Südlohn
    Südlohn is a municipality in western North Rhine-Westphalia, Germany, near the Dutch border.
  • D. Hohberg
    Hohberg is a municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
  • E. Schehring
    Schehring is an alternative spelling or variant name of Schering, a historic German pharmaceutical and chemical company known for its contributions to medicine and life sciences.
  • 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_69e0b51061388190aa03f19700d3ef04 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7333bd7a0819084bbd1d6c111bc65 completed April 21, 2026, 8:20 a.m.
Created at: April 16, 2026, 3:08 p.m.