Triple

T22922037
Position Surface form Disambiguated ID Type / Status
Subject Zheglov E568887 entity
Predicate employer P7 FINISHED
Object MUR NE NERFINISHED

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: MUR | Statement: [Zheglov, employer, MUR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MUR
Context triple: [Zheglov, employer, MUR]
  • A. MUR
    MUR is the Italian Ministry responsible for national policies on universities, higher education, and scientific and technological research.
  • B. MUR
    MUR is the stock ticker symbol for Murray & Roberts Holdings Ltd, a South African engineering and construction services company listed on the Johannesburg Stock Exchange.
  • C. MUR chosen
    MUR was a major French Resistance movement during World War II that unified several underground groups opposing the Nazi occupation and the Vichy regime.
  • D. MURR
    MURR is a high-power research nuclear reactor at the University of Missouri used for scientific research, isotope production, and educational purposes.
  • E. MOR
    MOR is the station code for Mo i Rana Station, a railway station in the town of Mo i Rana in Nordland county, Norway.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2458d90c88190a58cead4e781ca6a completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f180d6841c81908df6d4e501860a15 completed April 29, 2026, 3:53 a.m.
Created at: April 17, 2026, 3:43 p.m.