Triple

T27353103
Position Surface form Disambiguated ID Type / Status
Subject Hong Kong Station E685614 entity
Predicate connectedTo P37 FINISHED
Object Central Elevated Walkway System
The Central Elevated Walkway System is an extensive network of interconnected pedestrian bridges in Hong Kong’s Central district that links major commercial buildings, transport hubs, and public spaces above street level.
 E1769018 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: Central Elevated Walkway System | Statement: [Hong Kong Station, connectedTo, Central Elevated Walkway 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: Central Elevated Walkway System
Triple: [Hong Kong Station, connectedTo, Central Elevated Walkway System]
Generated description
The Central Elevated Walkway System is an extensive network of interconnected pedestrian bridges in Hong Kong’s Central district that links major commercial buildings, transport hubs, and public spaces above street level.

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, 11:49 a.m.