Triple

T1934324
Position Surface form Disambiguated ID Type / Status
Subject Cyber-shot E41410 entity
Predicate parentBrand P6092 FINISHED
Object Sony α E6422 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: Sony α | Statement: [Cyber-shot, parentBrand, Sony α]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sony α
Context triple: [Cyber-shot, parentBrand, Sony α]
  • A. Sony chosen
    Sony is a Japanese multinational conglomerate best known for its consumer electronics, gaming (PlayStation), entertainment, and imaging products.
  • B. Panasonic
    Panasonic is a major Japanese multinational electronics company known for its wide range of consumer electronics, home appliances, and industrial solutions.
  • C. Toshiba
    Toshiba is a major Japanese multinational conglomerate known for its electronics, semiconductors, and information technology products and services.
  • D. Sharp Corporation
    Sharp Corporation is a Japanese multinational electronics manufacturer known for its consumer electronics, display technologies, and home appliances.
  • E. Sony Semiconductor Solutions
    Sony Semiconductor Solutions is a Sony Group company that designs and manufactures semiconductor products, best known as a leading global producer of image sensors used in smartphones, cameras, and other electronic devices.
  • 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_69a88649b24c819080047f26b6db2ded completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb29b51408190afb2f918814e68c7 completed March 7, 2026, 5:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3f3932081909a72d1022259359e completed March 8, 2026, 10:10 p.m.
Created at: March 4, 2026, 7:35 p.m.