Triple

T35415539
Position Surface form Disambiguated ID Type / Status
Subject Route 8 E1023630 entity
Predicate partOf P40 FINISHED
Object Hong Kong strategic route system
The Hong Kong strategic route system is a network of major highways and expressways designed to facilitate efficient, high-capacity road transport across key urban and cross-harbour corridors in Hong Kong.
E990739 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 strategic route system | Statement: [Route 8, partOf, Hong Kong strategic route system]
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 strategic route system
Triple: [Route 8, partOf, Hong Kong strategic route system]
Generated description
The Hong Kong strategic route system is a network of major highways and expressways designed to facilitate efficient, high-capacity road transport across key urban and cross-harbour corridors in Hong Kong.

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_69f76df54bac8190bd0d3b0eb35cda5f completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7956bf3448190820a01108b63068a completed May 3, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a382cd5b3308190bb7184eb7a07f9e9 completed June 21, 2026, 6:26 p.m.
NEDg Description generation batch_6a382d377cc0819096c1f6470189d4dd completed June 21, 2026, 6:28 p.m.
NED2 Entity disambiguation (via description) batch_6a382da4155c8190a9a9a746cd92aec3 completed June 21, 2026, 6:29 p.m.
Created at: May 3, 2026, 4:03 p.m.