Triple

T11959818
Position Surface form Disambiguated ID Type / Status
Subject CMP Media E284637 entity
Predicate successor P78 FINISHED
Object UBM Tech E284638 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: UBM Tech | Statement: [CMP Media, successor, UBM Tech]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UBM Tech
Context triple: [CMP Media, successor, UBM Tech]
  • A. UBM Tech chosen
    UBM Tech was a business-to-business media and information company focused on the technology industry, known for publishing specialized tech publications and running industry events and conferences.
  • B. IDG World Expo
    IDG World Expo is a trade show and conference organizer known for producing major technology events and exhibitions worldwide.
  • C. Ziff-Davis Publishing Company
    Ziff-Davis Publishing Company is an American media and publishing firm best known for its influential magazines in science fiction, technology, and computing.
  • D. TechCrunch
    TechCrunch is a leading technology news website and media platform known for its coverage of startups, Silicon Valley, and the tech industry.
  • E. Computerworld
    Computerworld is a long-running information technology magazine and online publication focused on news, analysis, and insights for IT professionals and business technology leaders.
  • 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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9036941948190b150369094551731 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f4592fa9a48190a0450e3d0c57c4d3 completed May 1, 2026, 7:41 a.m.
Created at: April 8, 2026, 9:45 p.m.