Triple

T19376595
Position Surface form Disambiguated ID Type / Status
Subject E484683 entity
Predicate sinoVietnameseReading P120136 FINISHED
Object 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: hà | Statement: [河, sinoVietnameseReading, hà]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: sinoVietnameseReading
Context triple: [河, sinoVietnameseReading, hà]
  • A. hasVietnameseReading chosen
    Indicates that an entity is associated with a specific reading or pronunciation in the Vietnamese language.
  • B. mandarinReadingBopomofo
    Indicates the Bopomofo (Zhuyin) phonetic transcription used to represent the Mandarin pronunciation of a given expression or character.
  • C. VietnameseObjective
    Indicates that an entity serves as the goal, target, or object of an action or intention specifically related to Vietnam or the Vietnamese language, culture, or context.
  • D. koreanReadingHangul
    Indicates that an entity’s Korean reading is represented in Hangul script.
  • E. hasMandarinReading
    Indicates that an entity is associated with a specific reading or pronunciation in Mandarin Chinese.
  • 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_69d8e8d460d88190abf0591c5c9d2b0c completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e61a5cfbf48190ac60e3ffa6baa263 completed April 20, 2026, 12:21 p.m.
PD Predicate disambiguation batch_69e4fd54f8e48190956e73dd8969164a completed April 19, 2026, 4:05 p.m.
Created at: April 10, 2026, 1:35 p.m.