Triple

T9844844
Position Surface form Disambiguated ID Type / Status
Subject Yuri Milner E239313 entity
Predicate investedIn P17330 FINISHED
Object Xiaomi E321474 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: Xiaomi | Statement: [Yuri Milner, investedIn, Xiaomi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xiaomi
Context triple: [Yuri Milner, investedIn, Xiaomi]
  • A. Xiaomi chosen
    Xiaomi is a major Chinese electronics and smartphone manufacturer known for its affordable, feature-rich devices and rapidly growing global presence.
  • B. Vivo
    Vivo is an animated musical film produced by Sony Pictures Animation that follows a music-loving kinkajou on a heartfelt adventure to deliver a song.
  • C. Huawei
    Huawei is a major Chinese multinational technology company best known globally for its telecommunications equipment, smartphones, and role in 5G network infrastructure.
  • D. HTC
    HTC is a Taiwanese consumer electronics company best known for manufacturing smartphones and other mobile devices, including early Android and Windows-based phones.
  • E. Sony Mobile Communications
    Sony Mobile Communications is a former mobile phone division of Sony known for developing and marketing Xperia smartphones and related mobile devices.
  • 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_69ca84e3f0c48190ada72a65ebd50efd completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb35dc29c819080203be5b904dc9d completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5dda4b0819092703270e87bee5a completed April 5, 2026, 3:24 a.m.
Created at: March 30, 2026, 8:33 p.m.