Triple

T10482186
Position Surface form Disambiguated ID Type / Status
Subject Top Five E247199 entity
Predicate castMember P1668 FINISHED
Object Romany Malco E65280 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: Romany Malco | Statement: [Top Five, castMember, Romany Malco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Romany Malco
Context triple: [Top Five, castMember, Romany Malco]
  • A. Romany Malco chosen
    Romany Malco is an American actor and comedian best known for his roles in films like "The 40-Year-Old Virgin" and the TV series "A Million Little Things."
  • B. Joseph Markovitch
    Joseph Markovitch was the father of French photographer and painter Dora Maar, a key figure in the Surrealist movement and companion of Pablo Picasso.
  • C. Ormond Beatty
    Ormond Beatty was a 19th-century American educator and academic administrator best known for serving as president of Centre College in Kentucky.
  • D. Peter Facinelli
    Peter Facinelli is an American actor best known for playing Dr. Carlisle Cullen in the Twilight film series.
  • E. Moses Gunn
    Moses Gunn was an acclaimed American actor known for his powerful stage performances and notable film and television roles, including appearances in works like "Shaft" and "Roots."
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5095d21c08190a0b2f3e57fabb1d8 completed April 7, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8a03336988190bc1e61126fe576be completed April 10, 2026, 7:01 a.m.
Created at: April 6, 2026, 12:22 p.m.