Triple

T4747015
Position Surface form Disambiguated ID Type / Status
Subject Bundesplatz E105383 entity
Predicate connectsWith P37 FINISHED
Object Bundesgasse E422773 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: Bundesgasse | Statement: [Bundesplatz, connectsWith, Bundesgasse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bundesgasse
Context triple: [Bundesplatz, connectsWith, Bundesgasse]
  • A. Königsplatz
    Königsplatz is a central square in the Bavarian city of Fürth, Germany, known as an important local transport and urban hub.
  • B. Ballhausgasse
    Ballhausgasse is a street in central Vienna, Austria, located near the historic Ballhausplatz and the Austrian federal government district.
  • C. Friedrichstraße
    Friedrichstraße is a major central Berlin transport hub and historic thoroughfare known for its shopping, cultural venues, and role as a former border crossing during the Cold War.
  • D. Kochergasse chosen
    Kochergasse is a central street in Bern, Switzerland, situated in the government district close to the Federal Palace and other key federal institutions.
  • E. Savignyplatz
    Savignyplatz is a well-known square and surrounding neighborhood in Berlin’s Charlottenburg district, noted for its lively cafés, restaurants, and historic urban charm.
  • 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_69bd43f07fa48190954317d01600994a completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64c3fcb081909b1fe867b4adac8b completed March 20, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69be43b24440819081f3932eb6b68b48 completed March 21, 2026, 7:07 a.m.
Created at: March 20, 2026, 1:20 p.m.