Triple

T34681054
Position Surface form Disambiguated ID Type / Status
Subject A Chinese–English Dictionary (Herbert Giles, 1892) E890623 entity
Predicate romanizationOfHeadwords P125986 FINISHED
Object Wade–Giles 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: Wade–Giles | Statement: [A Chinese–English Dictionary (Herbert Giles, 1892), romanizationOfHeadwords, Wade–Giles]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: romanizationOfHeadwords
Context triple: [A Chinese–English Dictionary (Herbert Giles, 1892), romanizationOfHeadwords, Wade–Giles]
  • A. romanizationFrom
    Indicates that one entity is a romanized representation derived from the script or writing system of another entity.
  • B. romanizationType chosen
    Indicates the specific system or method used to convert text from one writing system into its Roman (Latin) alphabet representation.
  • C. romanizationVariantOf
    Indicates that one written form is a different romanized representation of the same underlying word or expression as another.
  • D. hasRomanizationOf
    Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
  • E. romanizedUnder
    Indicates that one written form is a romanized representation (using the Latin alphabet) of another form written in a different script.
  • 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_69f349dabc008190a18999c26682ed47 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7886be6d8819095ec62e4f2cee858 completed May 3, 2026, 5:39 p.m.
PD Predicate disambiguation batch_69f7841440f48190b4346c08855951d2 completed May 3, 2026, 5:21 p.m.
Created at: May 1, 2026, 2:05 a.m.