Triple

T11831484
Position Surface form Disambiguated ID Type / Status
Subject Tongyong Pinyin E281401 entity
Predicate hasDistinctSpellingFor P52133 FINISHED
Object zh, ch, sh initials compared to Hanyu Pinyin 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: zh, ch, sh initials compared to Hanyu Pinyin | Statement: [Tongyong Pinyin, hasDistinctSpellingFor, zh, ch, sh initials compared to Hanyu Pinyin]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasDistinctSpellingFor
Context triple: [Tongyong Pinyin, hasDistinctSpellingFor, zh, ch, sh initials compared to Hanyu Pinyin]
  • A. hasDistinctOrthographyFrom chosen
    Indicates that two written forms are orthographically different from each other, even if they may represent the same or related linguistic content.
  • B. hasVariantSpelling
    Indicates that one term is an alternative spelling form of another term.
  • C. hasDistinctLetterForms
    Indicates that the related writing system or symbol set uses different visual shapes or styles for the same letter in different contexts (such as position, case, or usage).
  • D. hasPronunciationDifferenceFrom
    Indicates that two linguistic items differ in how they are pronounced.
  • E. sharesSpellingWith
    Indicates that two entities have identical or substantially identical written forms (i.e., they are spelled the same way).
  • 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_69d6ab276f8c8190b1966a0ef11349ac completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a62c95988190a45dbaa7001c8846 completed April 10, 2026, 7:26 a.m.
PD Predicate disambiguation batch_69d8a251fc08819095933f1d13c3b742 completed April 10, 2026, 7:10 a.m.
Created at: April 8, 2026, 9:43 p.m.