Triple

T1686437
Position Surface form Disambiguated ID Type / Status
Subject Mikhail E36451 entity
Predicate equivalentName P6530 FINISHED
Object Mihajlo E55252 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: Mihajlo | Statement: [Mikhail, equivalentName, Mihajlo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mihajlo
Context triple: [Mikhail, equivalentName, Mihajlo]
  • A. Mihajlo chosen
    Mihajlo is the Serbian given name of Michael I. Pupin, the renowned Serbian-American physicist, inventor, and Columbia University professor.
  • B. Petar
    Petar is a given name commonly used in Slavic countries, equivalent to the English name Peter.
  • C. Miroslav
    Miroslav is a common Slavic male given name, notably borne by Slovak ice hockey star Miroslav Šatan.
  • D. Jovan Cvijić
    Jovan Cvijić was a prominent Serbian geographer and ethnologist known for his pioneering work on the geography and ethnography of the Balkan Peninsula.
  • E. Svetozar Boroević
    Svetozar Boroević was an Austro-Hungarian field marshal renowned for his defensive leadership on the Italian Front during World War I.
  • 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_69a886151508819084fa7f1ce6e05577 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa6293c368819094ab0f615e418647 completed March 6, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad79901458819098f0be72d9d4a9bb completed March 8, 2026, 1:28 p.m.
Created at: March 4, 2026, 7:29 p.m.