Triple

T21032563
Position Surface form Disambiguated ID Type / Status
Subject Vojvoda Sima Marković E518098 entity
Predicate givenName P17 FINISHED
Object Sima 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: Sima | Statement: [Vojvoda Sima Marković, givenName, Sima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sima
Context triple: [Vojvoda Sima Marković, givenName, Sima]
  • A. Sima chosen
    Sima is a Chinese surname historically associated with prominent figures such as the Song dynasty historian and statesman Sima Guang.
  • B. Sima Samar
    Sima Samar is an Afghan physician and human rights advocate renowned for her work promoting women's rights, education, and social justice in Afghanistan.
  • C. Sicong
    Sicong is a given name most notably associated with Ma Sicong, a prominent 20th-century Chinese composer and violinist.
  • D. Henao
    Henao is a Spanish-language surname most notably associated with Maria Victoria Henao, the widow of Colombian drug lord Pablo Escobar.
  • E. Gaochi
    Gaochi is the given name of Zhu Gaochi, the Ming dynasty emperor known posthumously as the Hongxi Emperor.
  • 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_69e0b503275c8190afd9a163f997c709 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc83828c81909c1ec745c0313c9f completed April 21, 2026, 4:26 a.m.
Created at: April 16, 2026, 1:56 p.m.