Triple

T21616012
Position Surface form Disambiguated ID Type / Status
Subject Lahntal railway E533438 entity
Predicate connects P390 FINISHED
Object Lahnstein 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: Lahnstein | Statement: [Lahntal railway, connects, Lahnstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lahnstein
Context triple: [Lahntal railway, connects, Lahnstein]
  • A. Lahnstein chosen
    Lahnstein is a historic town in western Germany, located on the Rhine River in the state of Rhineland-Palatinate.
  • B. Lahnau
    Lahnau is a municipality in the Lahn-Dill district of the German state of Hesse, known for its location near the cities of Wetzlar and Gießen.
  • C. Wuhletal
    Wuhletal is a valley landscape in Berlin shaped by the course of the Wuhle river, featuring green spaces, walking paths, and recreational areas.
  • D. Langenhain
    Langenhain is a district of the town Hofheim am Taunus in the German state of Hesse, known for its residential character and proximity to the Taunus hills.
  • E. Friedrichstein
    Friedrichstein is a district or neighborhood within the spa town of Bad Wildungen in the state of Hesse, 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_69e0c46411108190bba0d4176dffc9f3 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef3baab9e88190bc02f27133ef32d6 completed April 27, 2026, 10:34 a.m.
Created at: April 16, 2026, 6:33 p.m.