Triple

T20622907
Position Surface form Disambiguated ID Type / Status
Subject Static Age E506745 entity
Predicate hasTrack P3284 FINISHED
Object TV Casualty 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: TV Casualty | Statement: [Static Age, hasTrack, TV Casualty]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TV Casualty
Context triple: [Static Age, hasTrack, TV Casualty]
  • A. Casualty chosen
    Casualty is a long-running British medical drama television series centered on the staff and patients of a hospital emergency department.
  • B. Holby City
    Holby City is a long-running British medical drama television series set in a fictional hospital, focusing on the professional and personal lives of its staff.
  • C. TV Action
    TV Action was a British weekly comic magazine known for publishing adventure and science fiction strips based on popular television series.
  • D. Casualty–Holby franchise
    The Casualty–Holby franchise is a British television drama universe centered on interconnected medical series, most notably the long-running shows Casualty and its spin-off Holby City.
  • E. Casualty 1909
    Casualty 1909 is a British period medical drama series set in early 20th-century London, focusing on the lives and work of hospital staff and patients.
  • 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_69e0b4bc90988190ac360aaf645efc1d completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6abe3177c8190ad1b2ca8b1e0a560 completed April 20, 2026, 10:42 p.m.
Created at: April 16, 2026, 11:42 a.m.