Triple

T27353340
Position Surface form Disambiguated ID Type / Status
Subject Hong Kong Convention and Exhibition Centre E685619 entity
Predicate hostedEvent P613 FINISHED
Object Hong Kong Electronics Fair
The Hong Kong Electronics Fair is a major international trade show showcasing the latest consumer electronics, components, and technology innovations to global buyers and industry professionals.
E1769026 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: Hong Kong Electronics Fair | Statement: [Hong Kong Convention and Exhibition Centre, hostedEvent, Hong Kong Electronics Fair]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hong Kong Electronics Fair
Triple: [Hong Kong Convention and Exhibition Centre, hostedEvent, Hong Kong Electronics Fair]
Generated description
The Hong Kong Electronics Fair is a major international trade show showcasing the latest consumer electronics, components, and technology innovations to global buyers and industry professionals.

Provenance (5 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_69ef14887c288190931b8431fdbf53c4 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62c1b91e881908798e4f00723efcb completed May 2, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12a7d4786c8190881df8e944b7f868 completed May 24, 2026, 7:25 a.m.
NEDg Description generation batch_6a12a8b8ec608190846c55dabeec801a completed May 24, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_6a12a951f04881909419d5b9d41d5c79 completed May 24, 2026, 7:31 a.m.
Created at: April 27, 2026, 11:50 a.m.