Triple

T35003513
Position Surface form Disambiguated ID Type / Status
Subject Hung Hom Ferry Pier Bus Terminus E1009747 entity
Predicate operator P179 FINISHED
Object Cross-Harbour Bus
Cross-Harbour Bus is a Hong Kong bus company known for operating franchised routes that connect Kowloon and the New Territories with Hong Kong Island via cross-harbour tunnels.
 E2120301 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: Cross-Harbour Bus | Statement: [Hung Hom Ferry Pier Bus Terminus, operator, Cross-Harbour Bus]
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: Cross-Harbour Bus
Triple: [Hung Hom Ferry Pier Bus Terminus, operator, Cross-Harbour Bus]
Generated description
Cross-Harbour Bus is a Hong Kong bus company known for operating franchised routes that connect Kowloon and the New Territories with Hong Kong Island via cross-harbour tunnels.

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_69f76dcb716881909f75e4fd60ab2284 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f784e7a1ec819081e715158e50277e completed May 3, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37b293e458819080d32637acf52b05 completed June 21, 2026, 9:44 a.m.
NEDg Description generation batch_6a37b35f30b48190a2ef8bf97859463a completed June 21, 2026, 9:48 a.m.
NED2 Entity disambiguation (via description) batch_6a37b47166f48190a351377c2080628e completed June 21, 2026, 9:52 a.m.
Created at: May 3, 2026, 4:01 p.m.