Triple

T13894765
Position Surface form Disambiguated ID Type / Status
Subject Joshua Topolsky E334058 entity
Predicate employer P7 FINISHED
Object Engadget E66252 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: Engadget | Statement: [Joshua Topolsky, employer, Engadget]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Engadget
Context triple: [Joshua Topolsky, employer, Engadget]
  • A. Engadget chosen
    Engadget is a technology news and reviews website that covers consumer electronics, gadgets, and digital culture.
  • B. Gizmodo
    Gizmodo is a technology and design-focused news and opinion website known for its coverage of gadgets, science, and digital culture.
  • C. CNET
    CNET is a United States Navy command responsible for overseeing education and training programs for naval personnel.
  • D. Tekno
    Tekno is a Nigerian singer, songwriter, and record producer known for his Afrobeat and Afropop hit songs and dance-oriented sound.
  • E. MWC
    MWC is the commonly used abbreviation for Mennonite World Conference, a global community and fellowship of Anabaptist-related churches.
  • 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_69d81c5dd2d48190b7a5fc1e009de936 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de23a741908190bdf46d76c5f1411a completed April 14, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce7419cc81909488871c16d6b356 completed May 3, 2026, 10:38 p.m.
Created at: April 9, 2026, 10:15 p.m.