Triple

T19164904
Position Surface form Disambiguated ID Type / Status
Subject Miyun District E469153 entity
Predicate formerName P65 FINISHED
Object Miyun County NE NERFINISHED

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: Miyun County | Statement: [Miyun District, formerName, Miyun County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miyun County
Context triple: [Miyun District, formerName, Miyun County]
  • A. Miyun District chosen
    Miyun District is a suburban district in northeastern Beijing, China, known for its scenic reservoirs, mountains, and sections of the Great Wall.
  • B. Miyun Town
    Miyun Town is the main urban center and administrative seat of Beijing’s Miyun District, known as a local hub for commerce and services northeast of the city.
  • C. Shunyi District
    Shunyi District is a suburban district of Beijing known for hosting Beijing Capital International Airport and a mix of residential, industrial, and international community areas.
  • D. Chaoyang County
    Chaoyang County is an administrative county in northeastern China, governed by the prefecture-level city of Chaoyang in Liaoning Province.
  • E. Fuhai County
    Fuhai County is an administrative region in northern Xinjiang, China, known for its lakeside landscapes, pastoral economy, and proximity to the Kazakhstan border.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f15e2720819084b1707497db26a2 completed April 20, 2026, 9:26 a.m.
Created at: April 10, 2026, 12:06 p.m.