Triple

T14486645
Position Surface form Disambiguated ID Type / Status
Subject Badaling Wildlife World E359245 entity
Predicate locatedIn P40 FINISHED
Object Beijing Municipality E2312 NE 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: Beijing Municipality | Statement: [Badaling Wildlife World, locatedIn, Beijing Municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beijing Municipality
Context triple: [Badaling Wildlife World, locatedIn, 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. Tân An
    Tân An is a city in southern Vietnam that serves as an administrative, economic, and cultural hub in the Mekong Delta region.
  • D. 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.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8279740308190af9df93a3af8592e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de924ee0f08190baf68318b41fa64d completed April 14, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde163c3488190aac5a8bd769d5564 completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:20 a.m.