Triple

T26816349
Position Surface form Disambiguated ID Type / Status
Subject Lantau South Country Park E675128 entity
Predicate hasTrail P3625 FINISHED
Object Shek Pik Country Trail
Shek Pik Country Trail is a scenic hiking route on Lantau Island in Hong Kong, offering coastal and hillside views within the protected countryside.
E1790627 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: Shek Pik Country Trail | Statement: [Lantau South Country Park, hasTrail, Shek Pik Country Trail]
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: Shek Pik Country Trail
Triple: [Lantau South Country Park, hasTrail, Shek Pik Country Trail]
Generated description
Shek Pik Country Trail is a scenic hiking route on Lantau Island in Hong Kong, offering coastal and hillside views within the protected countryside.

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_69eee9b6b28481909332f83eb17e5170 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61a85eee481909550d515a5b8feea completed May 2, 2026, 3:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f6f8014481909c7352b6a9cd7e50 completed May 24, 2026, 1:02 p.m.
NEDg Description generation batch_6a12f79fed1c81908af492a3fd35f82d completed May 24, 2026, 1:05 p.m.
NED2 Entity disambiguation (via description) batch_6a12fbaac4c8819080293672dd321aa9 completed May 24, 2026, 1:22 p.m.
Created at: April 27, 2026, 4:52 a.m.