Triple

T4060364
Position Surface form Disambiguated ID Type / Status
Subject 颐和园 E86196 entity
Predicate 位于 P40 FINISHED
Object 北京市海淀区 E89575 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: 北京市海淀区 | Statement: [颐和园, 位于, 北京市海淀区]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 北京市海淀区
Context triple: [颐和园, 位于, 北京市海淀区]
  • A. Haidian District chosen
    Haidian District is a major urban district in northwest Beijing known for its universities, technology hubs, and historic imperial gardens.
  • B. Xicheng District, Beijing
    Xicheng District, Beijing is a central urban district of Beijing known for its historic neighborhoods, government institutions, and major cultural and financial landmarks.
  • C. Daxing District
    Daxing District is a rapidly developing suburban district in southern Beijing, China, known for hosting the major Beijing Daxing International Airport and large-scale urban expansion.
  • D. Changping District
    Changping District is a suburban district in the northern part of Beijing, China, known for its historical sites and scenic mountainous landscapes.
  • E. Dongcheng District, Beijing
    Dongcheng District, Beijing is a central urban district of China's capital city that encompasses many of its most important political, historical, and cultural landmarks, including Tiananmen Square and the Forbidden City.
  • 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_69aed93c69208190a4efac0efe3cd69b completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af01994b0c8190b34af36acadad5c6 completed March 9, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562a98c488190a7e77cd46ff998bc completed March 14, 2026, 1:29 p.m.
Created at: March 9, 2026, 3:38 p.m.