Triple

T2630734
Position Surface form Disambiguated ID Type / Status
Subject HMD Global E59624 entity
Predicate collaboratesWith P37 FINISHED
Object Foxconn E59361 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: Foxconn | Statement: [HMD Global, collaboratesWith, Foxconn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Foxconn
Context triple: [HMD Global, collaboratesWith, Foxconn]
  • A. Foxconn chosen
    Foxconn is a major Taiwanese multinational electronics manufacturer best known for assembling products for companies like Apple, including iPhones and other consumer devices.
  • B. Huawei
    Huawei is a major Chinese multinational technology company best known globally for its telecommunications equipment, smartphones, and role in 5G network infrastructure.
  • C. Toshiba
    Toshiba is a major Japanese multinational conglomerate known for its electronics, semiconductors, and information technology products and services.
  • D. Apple Inc.
    Apple Inc. is a multinational technology company best known for designing and selling consumer electronics like the iPhone, Mac, and iPad, along with software and digital services.
  • E. Fujitsu Limited
    Fujitsu Limited is a major Japanese multinational information and communications technology company known for its computing products, IT services, and 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_69ab4ac8596c8190b34997e73d9e991c completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8c567408190b94ff047efa4bc06 completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69af90a7021081909f81c4ddb48fa00c completed March 10, 2026, 3:31 a.m.
Created at: March 6, 2026, 9:50 p.m.