Triple

T1439327
Position Surface form Disambiguated ID Type / Status
Subject Checkpoint Charlie E31032 entity
Predicate near P350 FINISHED
Object Kochstraße E71197 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: Kochstraße | Statement: [Checkpoint Charlie, near, Kochstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kochstraße
Context triple: [Checkpoint Charlie, near, Kochstraße]
  • A. Kochstraße chosen
    Kochstraße is a Berlin U-Bahn station on line U6 located near Checkpoint Charlie in the central district of Kreuzberg.
  • B. Bad Tölz
    Bad Tölz is a Bavarian spa town in southern Germany known for its historic old town, alpine scenery, and traditional German architecture.
  • C. Waidmannslust
    Waidmannslust is a residential locality in the Reinickendorf borough of Berlin, Germany, known for its green spaces and suburban character.
  • D. Bad Mergentheim
    Bad Mergentheim is a historic spa town in the German state of Baden-Württemberg, renowned for its mineral springs and picturesque setting in the Tauber Valley.
  • E. Unter den Linden
    Unter den Linden is a historic and grand boulevard in central Berlin, Germany, renowned for its cultural institutions, landmarks, and role as a major ceremonial avenue.
  • 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_69a4991633388190a4d61b5a98aa407a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c506d5ac8190b4c5b394c6d3f414 completed March 1, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad08ba2cf88190a859bb0974761968 completed March 8, 2026, 5:27 a.m.
Created at: March 1, 2026, 8 p.m.