Triple

T14199245
Position Surface form Disambiguated ID Type / Status
Subject Bundesstraße 42 E351919 entity
Predicate connects P390 FINISHED
Object Lahnstein E214200 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: Lahnstein | Statement: [Bundesstraße 42, connects, Lahnstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lahnstein
Context triple: [Bundesstraße 42, 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. Waidberg
    Waidberg is a wooded hill and recreational area on the outskirts of Zurich, Switzerland, known for its hiking trails, viewpoints, and proximity to the Hönggerberg.
  • 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_69d827894ac0819097803e57f3227b23 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61f472548190a1a7edc40526eac3 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e72b9f08190a33e8e20541edd21 completed May 9, 2026, 12:23 a.m.
Created at: April 10, 2026, 1:04 a.m.