Triple

T9009016
Position Surface form Disambiguated ID Type / Status
Subject Neil Cross E215417 entity
Predicate notableWork P4 FINISHED
Object Spooks E199127 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: Spooks | Statement: [Neil Cross, notableWork, Spooks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Spooks
Context triple: [Neil Cross, notableWork, Spooks]
  • A. Spooks chosen
    Spooks is a British television spy drama series centered on the high-stakes operations of MI5 officers.
  • B. Line of Duty
    Line of Duty is a British crime drama television series that follows an anti-corruption police unit investigating complex and morally ambiguous cases within the force.
  • C. MI-5
    MI-5 is a British spy thriller film (also known as "Spooks: The Greater Good") based on the TV series "Spooks," featuring David Oyelowo in a prominent role.
  • D. Spies
    Spies is a German-origin surname most notably associated with August Spies, a prominent 19th-century anarchist and labor activist involved in the Haymarket affair.
  • E. Spies
    Spies is a novel by Michael Frayn that explores childhood memory, secrecy, and the blurred line between imagination and reality in wartime England.
  • 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_69ca83a2bf088190986ee7a8eb90407d completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69bed8588190afc9cbca12b75a3b completed April 1, 2026, 12:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb9a11948190a43f60d0df71b1af completed April 3, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:06 p.m.