Triple

T13827465
Position Surface form Disambiguated ID Type / Status
Subject Robert Pugh E332289 entity
Predicate name P16 FINISHED
Object Robert Pugh E332289 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: Robert Pugh | Statement: [Robert Pugh, name, Robert Pugh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robert Pugh
Context triple: [Robert Pugh, name, Robert Pugh]
  • A. Robert Pugh chosen
    Robert Pugh is a Welsh actor known for his extensive work in British film and television, including roles in series such as "Game of Thrones" and "Doctor Who."
  • B. Martin Pugh
    Martin Pugh is a British historian known for his influential works on modern British political and social history, including studies of the Labour Party, feminism, and interwar politics.
  • C. Cecil Poynton
    Cecil Poynton was an English footballer and long-serving full-back for Tottenham Hotspur during the early 20th century.
  • D. Peter Crompton
    Peter Crompton was a British physician and intellectual active in late 18th- and early 19th-century England, known for his involvement in scientific and reformist circles.
  • E. Robert Hutton
    Robert Hutton was an American film and television actor active from the 1940s through the 1970s, known for his roles in war dramas, science fiction, and comedies.
  • 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_69d81c5ae7c88190b0dd41bdafeb5999 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0295d2d48190b08eba0d805bd72d completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb6e3d048190869bba1b4a7e255f completed May 8, 2026, 3:04 p.m.
Created at: April 9, 2026, 10:13 p.m.