Triple

T5284591
Position Surface form Disambiguated ID Type / Status
Subject Bezirk Gera E119584 entity
Predicate borderedBy P224 FINISHED
Object Bezirk Erfurt E141527 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: Bezirk Erfurt | Statement: [Bezirk Gera, borderedBy, Bezirk Erfurt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bezirk Erfurt
Context triple: [Bezirk Gera, borderedBy, Bezirk Erfurt]
  • A. Bezirk Erfurt chosen
    Bezirk Erfurt was an administrative district of the former East Germany centered around the city of Erfurt and existing from the 1952 territorial reform until German reunification in 1990.
  • B. Bezirk Gera
    Bezirk Gera was an administrative district of the former East Germany, centered around the city of Gera in the state of Thuringia.
  • C. Bezirk Halle
    Bezirk Halle was an administrative district of the former East Germany, centered around the city of Halle and functioning as a key regional unit during the GDR era.
  • D. Bezirk Suhl
    Bezirk Suhl was an administrative district in the former East Germany, located in the southern part of the country and known for its mountainous Thuringian landscape and industrial centers.
  • E. Bezirk Leipzig
    Bezirk Leipzig was an administrative district in the former East Germany centered around the city of Leipzig.
  • 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_69bd446de5648190b313a90bd96730d2 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84d693288190b437955e40ad6abb completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf21aee16081909509f3b14b60a969 completed March 21, 2026, 10:54 p.m.
Created at: March 20, 2026, 1:52 p.m.