Triple

T27353564
Position Surface form Disambiguated ID Type / Status
Subject Tai Tam Reservoirs E685623 entity
Predicate locatedNear P294 FINISHED
Object Shek O Road
Shek O Road is a scenic coastal roadway on Hong Kong Island that winds through hilly terrain to connect urban areas with the beaches and villages of Shek O and its surrounding countryside.
E1769979 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 O Road | Statement: [Tai Tam Reservoirs, locatedNear, Shek O Road]
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 O Road
Triple: [Tai Tam Reservoirs, locatedNear, Shek O Road]
Generated description
Shek O Road is a scenic coastal roadway on Hong Kong Island that winds through hilly terrain to connect urban areas with the beaches and villages of Shek O and its surrounding 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_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_6a12a7d670308190ac810a4ec0683da9 completed May 24, 2026, 7:25 a.m.
NEDg Description generation batch_6a12a87492b48190be0461fafe4d081d completed May 24, 2026, 7:27 a.m.
NED2 Entity disambiguation (via description) batch_6a12a926a67c819083713f0245b3e299 completed May 24, 2026, 7:30 a.m.
Created at: April 27, 2026, 11:50 a.m.