Triple

T957105
Position Surface form Disambiguated ID Type / Status
Subject Gigafactory Nevada E20647 entity
Predicate associatedCompany P629 FINISHED
Object Panasonic E84596 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: Panasonic | Statement: [Gigafactory Nevada, associatedCompany, Panasonic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Panasonic
Context triple: [Gigafactory Nevada, associatedCompany, Panasonic]
  • A. Panasonic chosen
    Panasonic is a major Japanese multinational electronics company known for its wide range of consumer electronics, home appliances, and industrial solutions.
  • B. Sharp Corporation
    Sharp Corporation is a Japanese multinational electronics manufacturer known for its consumer electronics, display technologies, and home appliances.
  • C. Toshiba
    Toshiba is a major Japanese multinational conglomerate known for its electronics, semiconductors, and information technology products and services.
  • D. LG Electronics
    LG Electronics is a South Korean multinational electronics company known for producing a wide range of consumer electronics, home appliances, and mobile devices.
  • E. Mitsubishi Electric
    Mitsubishi Electric is a global Japanese electronics and electrical equipment manufacturer known for producing advanced technologies ranging from factory automation systems and power equipment to large-scale display and video board 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_69a493b21f2881908132dcf45dcd2f36 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3fac2bc8190a66feb70c68899b2 completed March 1, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac1cd72fe88190a7cdfe1afc123edd completed March 7, 2026, 12:40 p.m.
Created at: March 1, 2026, 7:40 p.m.