Triple

T15625588
Position Surface form Disambiguated ID Type / Status
Subject Mike and Dave Need Wedding Dates E375667 entity
Predicate starring P1507 FINISHED
Object Mary Holland E1028467 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: Mary Holland | Statement: [Mike and Dave Need Wedding Dates, starring, Mary Holland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary Holland
Context triple: [Mike and Dave Need Wedding Dates, starring, Mary Holland]
  • A. Mary Holland chosen
    Mary Holland is an American actress, comedian, and writer known for her work in television comedies and films, including co-writing and appearing in the holiday rom-com "Happiest Season."
  • B. Mary Ellis
    Mary Ellis was a British actress known for her work on stage and screen in the early to mid-20th century.
  • C. Mary Louisa
    Mary Louisa is the full given name of British journalist and political commentator Polly Toynbee.
  • D. Letitia Cropley
    Letitia Cropley is an eccentric parishioner in the British sitcom "The Vicar of Dibley," best known for her bizarre and unappetizing culinary creations.
  • E. Elizabeth Holwell
    Elizabeth Holwell was the wife of British colonial administrator and writer John Zephaniah Holwell, associated with the 18th-century British presence in India.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9e5e248190ae54cda1fde51efb completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff875e49748190a2a4aceb649762b4 completed May 9, 2026, 7:13 p.m.
Created at: April 10, 2026, 4:14 a.m.