Triple

T4060462
Position Surface form Disambiguated ID Type / Status
Subject Yíhéyuán E86197 entity
Predicate provinceLevelDivision P10770 FINISHED
Object Beijing Municipality E2312 NE FINISHED

How this triple was built (3 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: Beijing Municipality | Statement: [Yíhéyuán, provinceLevelDivision, Beijing Municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beijing Municipality
Context triple: [Yíhéyuán, provinceLevelDivision, Beijing Municipality]
  • A. Tianjin
    Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
  • B. Beijing chosen
    Beijing is the capital city of China, a major political, cultural, and economic center known for its rich history and rapid modern development.
  • C. Tiāntán
    Tiāntán is the Chinese pinyin name for the Temple of Heaven, a historic imperial religious complex in Beijing where Ming and Qing dynasty emperors performed annual ceremonies to pray for good harvests.
  • D. Zhongdu
    Zhongdu was the historical capital city of the Jurchen-led Jin dynasty in northern China, located in what is now part of modern Beijing.
  • E. Lingang
    Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: provinceLevelDivision
Context triple: [Yíhéyuán, provinceLevelDivision, Beijing Municipality]
  • A. countrySubdivision
    Indicates that one geopolitical region is an administrative or territorial subdivision of a larger country.
  • B. hasProvinceLevelUnit
    Indicates that one administrative or territorial entity possesses or contains a sub-unit at the province (or equivalent) level.
  • C. politicalDivision chosen
    Indicates that one entity is a governmental or administrative subdivision or jurisdiction within the territory or authority of another entity.
  • D. countrySubdivisionType
    Indicates the specific type or category of an administrative or territorial subdivision within a country (e.g., state, province, region).
  • E. mainProvinces
    Indicates that certain provinces are the primary or most significant administrative regions associated with a given entity.
  • F. None of above.

Provenance (4 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_69aed93c69208190a4efac0efe3cd69b completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefd0bdea48190805a79515ee92709 completed March 9, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576966bd081909b804a3ccc18c1ee completed March 14, 2026, 2:54 p.m.
PD Predicate disambiguation batch_69aef90438908190a005b08ba271eacf completed March 9, 2026, 4:44 p.m.
Created at: March 9, 2026, 3:38 p.m.