Triple

T6111010
Position Surface form Disambiguated ID Type / Status
Subject Checkpoint Charlie E136237 entity
Predicate locatedNear P294 FINISHED
Object Zimmerstraße E167095 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: Zimmerstraße | Statement: [Checkpoint Charlie, locatedNear, Zimmerstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zimmerstraße
Context triple: [Checkpoint Charlie, locatedNear, Zimmerstraße]
  • A. Zimmerstraße chosen
    Zimmerstraße is a street in central Berlin, Germany, historically significant for running along the former Berlin Wall and passing by the famous Checkpoint Charlie border crossing.
  • B. Siesmayerstraße
    Siesmayerstraße is a street in Frankfurt am Main, Germany, known for bordering the historic Palmengarten botanical garden.
  • C. Scharnweberstraße
    Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • D. Niederkirchnerstraße
    Niederkirchnerstraße is a street in central Berlin, Germany, historically associated with Nazi-era government and security offices and now home to memorial sites such as the Topography of Terror.
  • E. Grunerstraße
    Grunerstraße is a central street in Berlin located near Alexanderplatz, known for carrying heavy traffic through the city’s Mitte district.
  • 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_69c0089ea6f88190b349be53e04b4f5f completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05bbbbea88190b889a7c30af1d71a completed March 22, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64b9acb1c8190a51e540371e20bde completed March 27, 2026, 9:19 a.m.
Created at: March 22, 2026, 4:13 p.m.