Triple

T1650438
Position Surface form Disambiguated ID Type / Status
Subject Guangzhou Metro E35677 entity
Predicate ticketMedia P1303 FINISHED
Object single-journey token LITERAL 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: single-journey token | Statement: [Guangzhou Metro, ticketMedia, single-journey token]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: ticketMedia
Context triple: [Guangzhou Metro, ticketMedia, single-journey token]
  • A. fareMedia chosen
    Indicates that a particular type of ticket, pass, or payment instrument is used as the medium for paying a fare.
  • B. mediaType
    Indicates the format or category of media associated with an entity, such as text, image, audio, or video.
  • C. eligibleMedia
    Indicates that certain media items qualify under specified conditions or rules for participation, use, or consideration in a given context.
  • D. mediaWork
    Indicates a relationship where one entity is a media-related work (such as a film, book, recording, or other creative media production) associated with another entity.
  • E. mediaResponse
    Indicates that one entity serves as a reply or reaction in a media format (such as audio, video, or image) to another entity or communication.
  • F. None of above.

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_69a8860568888190a32cd9f70acbba42 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aaa0fbe984819084f8daee81ca9b67 completed March 6, 2026, 9:40 a.m.
PD Predicate disambiguation batch_69a907ce4dd881909168a1e99505d4ec completed March 5, 2026, 4:34 a.m.
Created at: March 4, 2026, 7:29 p.m.