Triple

T20541294
Position Surface form Disambiguated ID Type / Status
Subject Badachu Park E504339 entity
Predicate locatedIn P40 FINISHED
Object Shijingshan District 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: Shijingshan District | Statement: [Badachu Park, locatedIn, Shijingshan District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shijingshan District
Context triple: [Badachu Park, locatedIn, Shijingshan District]
  • A. Shijingshan District chosen
    Shijingshan District is an urban district in western Beijing, China, known for its industrial heritage, residential areas, and several notable historical and cultural sites.
  • B. Kecheng District
    Kecheng District is the central urban district and administrative seat of Quzhou City in Zhejiang Province, China.
  • C. Hongqiao District
    Hongqiao District is an urban administrative district of the municipality of Tianjin in northern China, known for its dense residential areas and commercial activity.
  • D. Longquanyi District
    Longquanyi District is an urban district of Chengdu in Sichuan Province, China, known for its rapid development and sports facilities.
  • E. Fengtai District
    Fengtai District is an urban district in southwestern Beijing, China, known for its mix of residential, industrial, and historical areas, including the site of the Marco Polo Bridge.
  • 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_69e0b4b476648190bc6019622ae54d3c completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a292dd1c8190b5c3031f3b44eb52 completed April 20, 2026, 10:02 p.m.
Created at: April 16, 2026, 11:37 a.m.