Triple

T11272957
Position Surface form Disambiguated ID Type / Status
Subject Ludvika E266858 entity
Predicate majorEmployer P588 FINISHED
Object ABB (historically) E84183 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: ABB (historically) | Statement: [Ludvika, majorEmployer, ABB (historically)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ABB (historically)
Context triple: [Ludvika, majorEmployer, ABB (historically)]
  • A. ABB chosen
    ABB is a multinational Swiss-Swedish corporation specializing in robotics, power, and automation technologies for utilities and industry.
  • B. General Electric
    General Electric is a major American multinational conglomerate historically known for its leadership in industrial manufacturing, aviation, power, and healthcare technologies.
  • C. Westinghouse Electric Corporation
    Westinghouse Electric Corporation was a major American manufacturing and broadcasting conglomerate known for its pioneering role in electrical equipment and its ownership of media assets such as NBC.
  • D. Eaton
    Eaton is a surname most notably associated with American decathlete and Olympic gold medalist Ashton Eaton.
  • E. Eaton
    Eaton is the namesake of the Eaton Professor of the Science of Government at Harvard University, an endowed academic chair in political science and government studies.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e965c9048190804ebb48f0a4817b completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f43633948190b86f5603ac50ec47 completed April 19, 2026, 3:26 p.m.
Created at: April 8, 2026, 9:31 p.m.