Triple

T3825963
Position Surface form Disambiguated ID Type / Status
Subject USZ E88690 entity
Predicate hasAbbreviation P43 FINISHED
Object USZ E88690 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: USZ | Statement: [USZ, hasAbbreviation, USZ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: USZ
Context triple: [USZ, hasAbbreviation, USZ]
  • A. USZ chosen
    USZ is a major public teaching hospital in Zurich, Switzerland, affiliated with the University of Zurich and known for its advanced medical care and research.
  • B. UZ
    UZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Uzbekistan.
  • C. USP
    USP is the largest and one of the most prestigious public universities in Brazil, renowned for its research output and academic excellence across a wide range of disciplines.
  • D. UzK
    UzK is the commonly used abbreviation for the University of Cologne, one of Germany’s largest and oldest universities.
  • E. USPD
    The USPD (Independent Social Democratic Party of Germany) was a left-wing socialist party in early 20th-century Germany that split from the SPD over opposition to World War I and later played a key role in the country’s revolutionary politics.
  • 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_69aed9538cf881909d9ce8ca4ac7c18c completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeeb64c72c8190b5f3d376aa4ee933 completed March 9, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb4f41c88190b3040236462c37cc completed March 14, 2026, 6:08 a.m.
Created at: March 9, 2026, 3:17 p.m.