Triple

T28904866
Position Surface form Disambiguated ID Type / Status
Subject London, Airstrip One E733043 entity
Predicate mediaControlInFiction P14447 FINISHED
Object complete state monopoly LITERAL 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: complete state monopoly | Statement: [London, Airstrip One, mediaControlInFiction, complete state monopoly]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mediaControlInFiction
Context triple: [London, Airstrip One, mediaControlInFiction, complete state monopoly]
  • A. mediaControl chosen
    Indicates a relationship where one entity directs, regulates, or influences the creation, distribution, or content of media controlled by another entity.
  • B. controlMedium
    Indicates that an entity regulates, directs, or influences another entity through a particular medium or channel.
  • C. mediaControlProtocol
    Indicates a protocol or method used to control the playback, routing, or management of media content between devices or systems.
  • D. fictionalMedium
    Indicates that a work of fiction is presented or conveyed through a particular medium or format (such as a book, film, game, or comic).
  • E. mediaConsumption
    Indicates the act or pattern of engaging with, using, or experiencing media content (such as watching, listening, or reading).
  • F. None of above.

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_69f05b096d208190958a57d2e4b5a93a completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f67d3624248190a36a9b2d2e9778d4 completed May 2, 2026, 10:39 p.m.
PD Predicate disambiguation batch_69f678ce54b081908c26edfd49e39c60 completed May 2, 2026, 10:21 p.m.
Created at: April 28, 2026, 8:06 a.m.