Triple

T17084539
Position Surface form Disambiguated ID Type / Status
Subject Network (screenplay) E414560 entity
Predicate title P38 FINISHED
Object Network E300953 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: Network | Statement: [Network (screenplay), title, Network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Network
Context triple: [Network (screenplay), title, Network]
  • A. Network
    Network is a National Hunt stallion best known as the sire of top-class jump racehorses, including the champion chaser Sprinter Sacre.
  • B. Network chosen
    Network is a 1976 satirical drama film directed by Sidney Lumet that critiques television news and media sensationalism.
  • C. NETWORK
    NETWORK is the radio callsign used by Network Aviation, an Australian regional airline operating charter and scheduled services.
  • D. Network World
    Network World is a technology-focused publication that covers computer networking news, analysis, and trends for IT professionals.
  • E. Networker
    Networker is a family of electric and diesel multiple-unit trains used on suburban and regional rail services in southeast 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_69d886cef44c8190ba56c44b4e863e64 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbe60d588190963ccd4c86af1233 completed April 18, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012ee651ec8190a37c5997f394d24b completed May 11, 2026, 1:20 a.m.
Created at: April 10, 2026, 5:35 a.m.