Triple

T9762885
Position Surface form Disambiguated ID Type / Status
Subject Counterpart E236710 entity
Predicate starring P1507 FINISHED
Object Harry Lloyd E440397 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: Harry Lloyd | Statement: [Counterpart, starring, Harry Lloyd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harry Lloyd
Context triple: [Counterpart, starring, Harry Lloyd]
  • A. Harry Lloyd chosen
    Harry Lloyd is an English actor known for his roles in television series such as Robin Hood and Game of Thrones, as well as various film and stage productions.
  • B. Hugh Lloyd
    Hugh Lloyd was a British character actor and comedian best known for his work in mid-20th-century film and television, particularly in comic roles.
  • C. Lewis Pullman
    Lewis Pullman is an American actor known for roles in films such as "Top Gun: Maverick," "Bad Times at the El Royale," and "The Strangers: Prey at Night."
  • D. Peter Macon
    Peter Macon is an American actor best known for playing the Moclan officer Lt. Cmdr. Bortus on the science fiction comedy-drama series "The Orville."
  • E. Mitchell Henry
    Mitchell Henry was a 19th-century British politician, businessman, and newspaper proprietor who played a key role in the early development of regional journalism in Manchester.
  • 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_69ca84d64f6c8190a4ed4e9f5936eda5 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda09d8bc88190808145f141b4a9f8 completed April 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc46f170819081ecc5e85a0514c3 completed April 5, 2026, 2:43 a.m.
Created at: March 30, 2026, 8:25 p.m.