Triple

T11324558
Position Surface form Disambiguated ID Type / Status
Subject Kwang-chou E268174 entity
Predicate hostsEvent P613 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: [Kwang-chou, hostsEvent, Canton Fair]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canton Fair
Context triple: [Kwang-chou, hostsEvent, 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. China–ASEAN Expo
    The China–ASEAN Expo is a major annual trade and investment fair that promotes economic cooperation and integration between China and the member states of the Association of Southeast Asian Nations.
  • C. Hannover Messe
    Hannover Messe is one of the world’s largest and most influential industrial technology trade fairs, held annually in Hanover, Germany.
  • D. Berliner Messe
    Berliner Messe is a minimalist sacred choral composition by Estonian composer Arvo Pärt, written in his signature tintinnabuli style for the Latin Mass.
  • E. Messe Düsseldorf
    Messe Düsseldorf is a major international trade fair and exhibition center in Düsseldorf, Germany, hosting numerous global industry events and conventions.
  • 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_69d6aacb1f0881908c84a349fd1be047 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9e122e48190b3f890de8d561480 completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e525fb8d74819089d1505d1f0f116c completed April 19, 2026, 6:59 p.m.
Created at: April 8, 2026, 9:32 p.m.