Triple

T3677913
Position Surface form Disambiguated ID Type / Status
Subject Mulhouse E78039 entity
Predicate twinCity P1072 FINISHED
Object Chemnitz E1679 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: Chemnitz | Statement: [Mulhouse, twinCity, Chemnitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chemnitz
Context triple: [Mulhouse, twinCity, Chemnitz]
  • A. Chemnitz chosen
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • B. Zwickau
    Zwickau is a city in the German state of Saxony known historically as an important center of the automotive industry and as the birthplace of composer Robert Schumann.
  • C. Zittau
    Zittau is a historic town in the southeastern corner of Germany, known for its proximity to both the Czech and Polish borders and its well-preserved medieval architecture.
  • D. Dresden
    Dresden is a small community within the municipality of Chatham-Kent in southwestern Ontario, Canada, known historically for its role in the Underground Railroad and Black settlement.
  • E. Dresden
    Dresden is a historic cultural and economic center in eastern Germany, renowned for its baroque architecture, art collections, and reconstruction after World War II.
  • 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_69ad85e18c1c8190be8aafb227f39f48 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc46599188190a046eddb0d85c483 completed March 8, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4379623c8190856b03238e3ef0dd completed March 21, 2026, 7:06 a.m.
Created at: March 8, 2026, 3:25 p.m.