Triple

T2419123
Position Surface form Disambiguated ID Type / Status
Subject Mike Markkula E52377 entity
Predicate givenName P17 FINISHED
Object Armas E235038 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: Armas | Statement: [Mike Markkula, givenName, Armas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Armas
Context triple: [Mike Markkula, givenName, Armas]
  • A. Armas chosen
    Armas is a Finnish given name, notably used as one of the names of the renowned Finnish poet Eino Leino.
  • B. Fussilat
    Fussilat is the 41st chapter of the Qur’an, known for its detailed exposition of divine revelation, signs in creation, and the consequences of accepting or rejecting the message.
  • C. Termunten
    Termunten is a small village in the province of Groningen in the northeastern Netherlands, situated near the Ems estuary and the Wadden Sea.
  • D. Aasrud
    Aasrud is a Norwegian surname most notably borne by politician Rigmor Aasrud.
  • E. ARMIR
    ARMIR was the Italian 8th Army deployed on the Eastern Front during World War II, best known for its disastrous defeat alongside German forces in the Soviet Union.
  • 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_69ab495622948190bc6bc6e4cddaf645 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc96e1b3881909de57501b5d4099a completed March 7, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf5397508190b755e522060041c0 completed March 9, 2026, 12:38 p.m.
Created at: March 6, 2026, 9:42 p.m.