Triple

T23051168
Position Surface form Disambiguated ID Type / Status
Subject Sacha Kljestan E574017 entity
Predicate givenName P17 FINISHED
Object Sacha 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: Sacha | Statement: [Sacha Kljestan, givenName, Sacha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sacha
Context triple: [Sacha Kljestan, givenName, Sacha]
  • A. Sacha chosen
    Sacha is a given name used in various cultures, often as a variant of Sasha and commonly serving as a diminutive of Alexander or Alexandra.
  • B. Sapajus
    Sapajus is a genus of robust capuchin monkeys native to Central and South America, known for their high intelligence, tool use, and complex social behavior.
  • C. Simao
    Simao is the former name of Pu'er, a city in Yunnan Province, China, historically known for its tea trade.
  • D. San Simon
    San Simon is a municipality in the province of Pampanga in the Philippines, known for its agricultural economy and proximity to major urban centers in Central Luzon.
  • E. Tarqui
    Tarqui is a locality in southern Ecuador historically notable as the site of the 1829 Battle of Tarqui between Gran Colombia and Peru.
  • 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_69e245ba7ae48190be606dbc54120e39 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1867c443081909588262bc90748af completed April 29, 2026, 4:18 a.m.
Created at: April 17, 2026, 3:54 p.m.