Triple

T2464166
Position Surface form Disambiguated ID Type / Status
Subject Canton E55203 entity
Predicate hosts P186 FINISHED
Object Canton Fair E35220 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: Canton Fair | Statement: [Canton, hosts, Canton Fair]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canton Fair
Context triple: [Canton, hosts, Canton Fair]
  • A. Canton Fair chosen
    The Canton Fair is China’s largest and oldest trade fair, held biannually in Guangzhou and serving as a major global platform for importing and exporting a wide range of goods.
  • B. Hannover Messe
    Hannover Messe is one of the world’s largest and most influential industrial technology trade fairs, held annually in Hanover, Germany.
  • C. Messe Düsseldorf
    Messe Düsseldorf is a major international trade fair and exhibition center in Düsseldorf, Germany, hosting numerous global industry events and conventions.
  • D. Salon du Bourget
    Salon du Bourget is the French name for the Paris Air Show, one of the world’s largest and oldest international aerospace industry exhibitions held at Le Bourget Airport near Paris.
  • E. Leipzig Trade Fair (Leipziger Messe)
    Leipzig Trade Fair (Leipziger Messe) is one of the world’s oldest and most prominent trade fair organizations, hosting major international exhibitions and conferences in Leipzig, Germany.
  • 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_69ab49e3622c8190ad22afa2c4fbb807 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd12059788190a6493f64bb725aed completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0d6ed7481909e900f947463d5d8 completed March 9, 2026, 4:09 p.m.
Created at: March 6, 2026, 9:44 p.m.