Triple

T20744714
Position Surface form Disambiguated ID Type / Status
Subject The Blue Lamp E510548 entity
Predicate character P662 FINISHED
Object PC George Dixon NE NERFINISHED

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: PC George Dixon | Statement: [The Blue Lamp, character, PC George Dixon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PC George Dixon
Context triple: [The Blue Lamp, character, PC George Dixon]
  • A. PC George Dixon chosen
    PC George Dixon is a fictional, archetypal British police constable who became a beloved symbol of steady, community-focused policing in mid-20th-century UK film and television.
  • B. PC Andy Mitchell
    PC Andy Mitchell is a fictional police constable featured in the British crime film "The Blue Lamp."
  • C. PC Fancy Smith
    PC Fancy Smith is a central police constable character in the long-running British television drama series "Z-Cars."
  • D. PC Joe Penhale
    PC Joe Penhale is a bumbling yet well-meaning village police officer in the British television series "Doc Martin."
  • E. PC Franeker
    PC Franeker is one of the most prestigious and historic Frisian handball tournaments, held annually in Franeker, the Netherlands.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c845e88190b4c5f3ae79291182 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c21197088190951a4c4a7e765891 completed April 21, 2026, 12:17 a.m.
Created at: April 16, 2026, 12:33 p.m.