Triple

T10465665
Position Surface form Disambiguated ID Type / Status
Subject Green Man E246786 entity
Predicate hasContributor P4244 FINISHED
Object Phil Thornalley E868764 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: Phil Thornalley | Statement: [Green Man, hasContributor, Phil Thornalley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phil Thornalley
Context triple: [Green Man, hasContributor, Phil Thornalley]
  • A. Phil Thornalley chosen
    Phil Thornalley is a British songwriter, record producer, and musician best known for his work with artists like The Cure and Natalie Imbruglia.
  • B. Phil Anderson
    Phil Anderson is an Australian former professional road cyclist renowned as one of the leading stage racers of the 1980s and the first non-European to wear the Tour de France yellow jersey.
  • C. Ian Walters
    Ian Walters was a British sculptor best known for his politically engaged public monuments, including prominent statues of anti-apartheid leader Nelson Mandela.
  • D. Roy Marples
    Roy Marples is a software engineer best known for his work on the OpenRC init system and various networking tools in the Linux and BSD ecosystems.
  • E. Neil Hartley
    Neil Hartley is a film and television producer known for his work on the adaptation of "The Go-Between."
  • 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_69d381c16c248190a2fe5b471e584e9c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5092d6d408190b6bda4d7ced4601e completed April 7, 2026, 1:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69d933b40ff8819097e994a496228b7d completed April 10, 2026, 5:30 p.m.
Created at: April 6, 2026, 12:19 p.m.