Triple

T12627115
Position Surface form Disambiguated ID Type / Status
Subject iPhone 13 E301543 entity
Predicate supportsLocation P29891 FINISHED
Object BeiDou E141895 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: BeiDou | Statement: [iPhone 13, supportsLocation, BeiDou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BeiDou
Context triple: [iPhone 13, supportsLocation, BeiDou]
  • A. BeiDou chosen
    BeiDou is China's satellite-based global navigation system that serves as an alternative to and competitor of GPS.
  • B. Galileo satellite navigation system
    The Galileo satellite navigation system is the European Union’s global navigation satellite system designed to provide highly accurate positioning and timing services worldwide as an independent alternative to GPS and other GNSS constellations.
  • C. Tianhe
    Tianhe is the core module of China’s Tiangong space station, serving as its main control, living, and docking hub in low Earth orbit.
  • D. Tianhe
    Tianhe is a town in Wuhan, Hubei Province, China, best known for hosting Wuhan Tianhe International Airport, a major air transport hub in central China.
  • E. Tsinan
    Tsinan is an older romanized name for Jinan, the capital city of Shandong Province in eastern China known for its numerous natural springs.
  • 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_69d7bdeaf49c8190b13800111fa77ea3 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9610b91dc8190a9abefb88447b0ae completed April 10, 2026, 8:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ed8d81c8190baed4292ce3a74a1 completed May 2, 2026, 8:30 p.m.
Created at: April 9, 2026, 5:14 p.m.