Triple

T10669656
Position Surface form Disambiguated ID Type / Status
Subject Xicheng District, Beijing E251452 entity
Predicate contains P35 FINISHED
Object Shichahai E389251 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: Shichahai | Statement: [Xicheng District, Beijing, contains, Shichahai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shichahai
Context triple: [Xicheng District, Beijing, contains, Shichahai]
  • A. Shichahai chosen
    Shichahai is a historic scenic area in central Beijing known for its interconnected lakes, traditional hutong neighborhoods, and vibrant cultural and leisure activities.
  • B. Yachimun
    Yachimun is the traditional Okinawan pottery style known for its rustic forms, vivid glazes, and deep roots in Ryukyuan culture and craftsmanship.
  • C. Chikushino
    Chikushino is a city in southwestern Japan known as a residential and commercial hub within the Fukuoka metropolitan area.
  • D. Shikaoi
    Shikaoi is a rural town in Hokkaido, Japan, known for its natural scenery, agriculture, and access to outdoor activities such as hiking and hot springs.
  • E. Oimachi
    Oimachi is a commercial and residential district in Tokyo known for its busy train hub, shopping streets, and convenient access to central Shinagawa and other parts of the 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_69d6aa5b0d2881909584b20efc5877f0 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6f861513881909b44c711371086b7 completed April 9, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb07626988190a46d8a54eda156f5 completed April 14, 2026, 9:24 p.m.
Created at: April 8, 2026, 9:09 p.m.