Triple

T15483621
Position Surface form Disambiguated ID Type / Status
Subject Honor Swinton Byrne E376984 entity
Predicate givenName P17 FINISHED
Object Honor E1140827 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: Honor | Statement: [Honor Swinton Byrne, givenName, Honor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Honor
Context triple: [Honor Swinton Byrne, givenName, Honor]
  • A. Honor chosen
    Honor is a given name of English origin that conveys the qualities of respect, integrity, and high moral character.
  • B. Honour
    Honour is a British television drama series that explores the real-life investigation into the 2006 honour killing of Banaz Mahmod.
  • C. Honor (historical)
    Honor (historical) is a former smartphone and electronics brand that was created and owned by Huawei, targeting younger consumers with competitively priced devices before being sold off in 2020.
  • D. Honor and Excellence
    Honor and Excellence is the guiding motto of the University of the Philippines, emphasizing integrity and academic distinction as core values of the institution.
  • E. honour
    Honour is a moral principle centered on personal integrity, duty, and reputation, often driving individuals to uphold what is right even at great personal cost.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f8e6ff08190b130b3a38f4190e7 completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2d0f4e648190b9cd9b1464209224 completed May 9, 2026, 12:48 p.m.
Created at: April 10, 2026, 3:45 a.m.