Triple

T2794751
Position Surface form Disambiguated ID Type / Status
Subject Ericsson E53008 entity
Predicate competitor P1375 FINISHED
Object ZTE E61920 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: ZTE | Statement: [Ericsson, competitor, ZTE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ZTE
Context triple: [Ericsson, competitor, ZTE]
  • A. ZTE chosen
    ZTE is a major Chinese telecommunications and technology company known for manufacturing network equipment and smartphones and competing globally with firms like Nokia and Huawei.
  • 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. Alcatel
    Alcatel is a multinational telecommunications equipment and networking company known for providing infrastructure, mobile, and broadband solutions worldwide.
  • D. Nokia
    Nokia is a Finnish multinational telecommunications and consumer electronics company best known for its historic leadership in mobile phones and its current focus on network infrastructure and 5G technologies.
  • E. Motorola
    Motorola is an American telecommunications and semiconductor company best known for pioneering mobile phones and designing influential microprocessors like the 68000 family.
  • 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_69ab495a90788190941b6917e1eca3a6 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abddd48bcc819083f4ec59d66f0ece completed March 7, 2026, 8:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8a5c364819092b01e90ee40e155 completed March 10, 2026, 9:47 a.m.
Created at: March 6, 2026, 9:58 p.m.