Triple

T36155356
Position Surface form Disambiguated ID Type / Status
Subject Lady Yugao E1045714 entity
Predicate meetsGenji P1220 FINISHED
Object through an exchange of poems involving a fan and a fence with yūgao flowers 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: through an exchange of poems involving a fan and a fence with yūgao flowers | Statement: [Lady Yugao, meetsGenji, through an exchange of poems involving a fan and a fence with yūgao flowers]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: meetsGenji
Context triple: [Lady Yugao, meetsGenji, through an exchange of poems involving a fan and a fence with yūgao flowers]
  • A. meets chosen
    Indicates that two or more entities come together at the same place and time, typically for interaction or a shared purpose.
  • B. meetsTo
    Indicates that one entity comes together with another at a specific time and place for an encounter, appointment, or interaction.
  • C. meetsAs
    Indicates that two entities encounter or come together at the same place and time, typically in a planned or recognized interaction.
  • D. meetsRegarding
    Indicates that one entity meets with another specifically to discuss or address a particular topic, issue, or subject.
  • E. meetsType
    Indicates that one entity encounters or comes into contact with another entity in a particular manner or context.
  • 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_69f76e38903c8190a52887620f90aabe completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b69b333081909cadbed3fcb8ecf5 completed May 3, 2026, 8:56 p.m.
PD Predicate disambiguation batch_69f7b4c2a5f8819094ad4621d7b97e0c completed May 3, 2026, 8:49 p.m.
Created at: May 3, 2026, 4:08 p.m.