Triple

T25428446
Position Surface form Disambiguated ID Type / Status
Subject 啟臣 E637183 entity
Predicate possibleRomanizationSystem P125986 FINISHED
Object Hanyu Pinyin NE NERFINISHED

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: Hanyu Pinyin | Statement: [啟臣, possibleRomanizationSystem, Hanyu Pinyin]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: possibleRomanizationSystem
Context triple: [啟臣, possibleRomanizationSystem, Hanyu Pinyin]
  • A. hasRomanizationOf
    Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
  • B. romanizationType chosen
    Indicates the specific system or method used to convert text from one writing system into its Roman (Latin) alphabet representation.
  • C. exampleRomanization
    Indicates that one entity is a romanized representation (in Latin script) of the other entity’s original text or name.
  • D. hasRomanizationStandard
    Indicates that an entity’s romanized form follows a specified romanization standard or system.
  • E. romanizationVariantOf
    Indicates that one written form is a different romanized representation of the same underlying word or expression as another.
  • 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_69e75db58a1c8190891b9ff7c2f8414e completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f60c3b09488190ade1b69ff7f0df0e completed May 2, 2026, 2:37 p.m.
PD Predicate disambiguation batch_69f60b8461ac81908c5bd3d73eed59f4 completed May 2, 2026, 2:34 p.m.
Created at: April 21, 2026, 1:58 p.m.