Triple

T4051369
Position Surface form Disambiguated ID Type / Status
Subject OLED TV E84592 entity
Predicate producedBy P490 FINISHED
Object Sony (various models) 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 (various models) | Statement: [OLED TV, producedBy, Sony (various models)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sony (various models)
Context triple: [OLED TV, producedBy, Sony (various models)]
  • A. Sony chosen
    Sony is a Japanese multinational conglomerate best known for its consumer electronics, gaming (PlayStation), entertainment, and imaging products.
  • B. Bravia
    Bravia is Sony's line of high-definition televisions and display products known for their advanced picture and sound technologies.
  • C. PlayStation
    PlayStation is a popular line of video game consoles and gaming platforms developed by Sony, known for its extensive library of exclusive titles and global influence on the gaming industry.
  • D. Sony Assurance
    Sony Assurance is a Japanese insurance company under the Sony Financial Group, offering primarily automobile and other personal insurance services.
  • E. Panasonic
    Panasonic is a major Japanese multinational electronics company known for its wide range of consumer electronics, home appliances, and industrial solutions.
  • 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_69aed933bec881909edfa28ebb69c634 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb8539148190990468c1429be9dd completed March 9, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b55659256081909154569cedd1694a completed March 14, 2026, 12:36 p.m.
Created at: March 9, 2026, 3:37 p.m.