Triple

T1602306
Position Surface form Disambiguated ID Type / Status
Subject Phones 4u Arena E34420 entity
Predicate namedAfter P63 FINISHED
Object Phones 4u E181334 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: Phones 4u | Statement: [Phones 4u Arena, namedAfter, Phones 4u]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phones 4u
Context triple: [Phones 4u Arena, namedAfter, Phones 4u]
  • A. Phones 4u chosen
    Phones 4u was a UK-based mobile phone retailer known for its high-street stores and prominent brand marketing before going into administration in 2014.
  • B. Phones 4u Arena
    Phones 4u Arena was the sponsored name, from 2013 to 2015, of the large indoor entertainment and sports venue in Manchester now commonly known as Manchester Arena.
  • C. Fitel
    Fitel was a financial technology startup where Jeff Bezos worked early in his career, before joining D. E. Shaw and later founding Amazon.
  • D. Breeze Mobile
    Breeze Mobile is a mobile ticketing and payment app used by the Metropolitan Atlanta Rapid Transit Authority (MARTA) for accessing public transit services in the Atlanta area.
  • E. ZTE
    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.
  • 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_69a885fea6a481909fe83ba6441f1774 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62292d1c819080b597199dc6b8d5 completed March 6, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad51bcdebc81909520786c560598b6 completed March 8, 2026, 10:38 a.m.
Created at: March 4, 2026, 7:28 p.m.