Triple

T10080566
Position Surface form Disambiguated ID Type / Status
Subject William Avery Bishop E213887 entity
Predicate hasHonorificSuffix P341 FINISHED
Object MC E25585 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: MC | Statement: [William Avery Bishop, hasHonorificSuffix, MC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MC
Context triple: [William Avery Bishop, hasHonorificSuffix, MC]
  • A. MC chosen
    MC is the postnominal abbreviation used to denote recipients of the Military Cross, a British military decoration awarded for gallantry during active operations against the enemy.
  • B. MC
    MC is a hip-hop master of ceremonies responsible for rapping, hosting, and energizing a crowd during performances or events.
  • C. MC
    MC is the commonly used abbreviation for Middlesex College, a public community college located in New Jersey.
  • D. MC
    MC is the Italian vehicle registration code assigned to the province of Macerata in the Marche region.
  • E. MC
    MC is the two-letter ISO 3166 country code for Monaco, the small sovereign city-state on the French Riviera known for its wealth, casinos, and the Monte Carlo district.
  • 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_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd032ef288190a961d266d9ecafbc completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b660987c8190a6a29d9e56acbff7 completed April 5, 2026, 7:22 p.m.
Created at: March 30, 2026, 9 p.m.