Triple

T15290697
Position Surface form Disambiguated ID Type / Status
Subject Daizong E365517 entity
Predicate region P40 FINISHED
Object China E5561 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: China | Statement: [Daizong, region, China]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: China
Context triple: [Daizong, region, China]
  • A. China chosen
    China is a vast East Asian country known for its long continuous civilization, large population, and major global economic and political influence.
  • B. Kinas
    Kinas is the official rooster mascot created for the UEFA Euro 2004 football championship held in Portugal.
  • C. Çine
    Çine is a district and town in southwestern Turkey known for its agricultural activities and location within Aydın Province in the Aegean region.
  • D. Chung Kuo
    "Chung Kuo" is an instrumental electronic music track by Vangelis from his 1979 album "China," evoking an atmospheric, synthesizer-driven portrait of China.
  • E. kina
    Kina is the official currency of Papua New Guinea, used for everyday transactions and financial activities throughout the country.
  • 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_69d85a103d9081908c1ea6c4c73ac8e3 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03680b60c8190a3ea54a9d34c8105 completed April 16, 2026, 1:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69feef6a5ad48190a13f0b7bc1a6be0b completed May 9, 2026, 8:25 a.m.
Created at: April 10, 2026, 3:15 a.m.