Triple

T1774632
Position Surface form Disambiguated ID Type / Status
Subject Motorola E38949 entity
Predicate acquiredBy P347 FINISHED
Object Lenovo E72301 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: Lenovo | Statement: [Motorola, acquiredBy, Lenovo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lenovo
Context triple: [Motorola, acquiredBy, Lenovo]
  • A. Lenovo chosen
    Lenovo is a multinational technology company best known for manufacturing and selling personal computers, laptops, smartphones, and other consumer electronics worldwide.
  • B. Acer
    Acer is a Taiwanese multinational hardware and electronics corporation best known for manufacturing laptops, desktops, monitors, and other computer-related products.
  • C. Dell
    Dell is a major American technology company best known for designing, manufacturing, and selling personal computers, servers, and related IT products and services worldwide.
  • D. Compaq
    Compaq was a major American computer company best known for its popular line of personal computers and for being one of the largest PC manufacturers before its acquisition by Hewlett-Packard.
  • E. Toshiba
    Toshiba is a major Japanese multinational conglomerate known for its electronics, semiconductors, and information technology products and services.
  • 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_69a8862e61708190af97b9838cc3f5de completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64b6c4a88190ab2f75c8d4814f11 completed March 6, 2026, 5:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada9982d208190b0c29ee1141e91b0 completed March 8, 2026, 4:53 p.m.
Created at: March 4, 2026, 7:31 p.m.