Triple

T15459432
Position Surface form Disambiguated ID Type / Status
Subject Liu E371857 entity
Predicate rankAmongChineseSurnames P29278 FINISHED
Object one of the most common Chinese surnames 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: one of the most common Chinese surnames | Statement: [Liu, rankAmongChineseSurnames, one of the most common Chinese surnames]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: rankAmongChineseSurnames
Context triple: [Liu, rankAmongChineseSurnames, one of the most common Chinese surnames]
  • A. rankingByLengthInChina
    Indicates that entities are ordered or evaluated based on their length within the context of China.
  • B. nameOrderInChinese
    Indicates that the entities are arranged in the order that personal names are written or spoken in Chinese (family name first, given name second).
  • C. isAmongMostCommonSurnamesIn chosen
    Indicates that a surname ranks within the group of most frequently occurring surnames in a specified region or population.
  • D. rankInChineseAdministrativeHierarchy
    Indicates the relative level or position an administrative unit holds within the formal hierarchy of Chinese government administration.
  • E. nameInMcCuneReischauer
    Indicates that an entity’s name is represented using the McCune–Reischauer romanization system.
  • 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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f1623f0819086f6fc2bfd536609 completed April 16, 2026, 1:44 a.m.
PD Predicate disambiguation batch_69ded284bd008190b31c53b4f1cebadd completed April 14, 2026, 11:49 p.m.
Created at: April 10, 2026, 3:32 a.m.