Triple

T26649082
Position Surface form Disambiguated ID Type / Status
Subject Woodlands Bus Interchange E668998 entity
Predicate zoning P727 FINISHED
Object North Region bus network
The North Region bus network is a public bus system serving Singapore’s northern residential and commercial districts, providing connectivity between towns such as Woodlands, Yishun, and Sembawang and key transport hubs.
 E1733633 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: North Region bus network | Statement: [Woodlands Bus Interchange, zoning, North Region bus network]
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: North Region bus network
Triple: [Woodlands Bus Interchange, zoning, North Region bus network]
Generated description
The North Region bus network is a public bus system serving Singapore’s northern residential and commercial districts, providing connectivity between towns such as Woodlands, Yishun, and Sembawang and key transport hubs.

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_69ee9d00eb5481908d6c6d0ada2f0c9a completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f6167875e8819083782aec7b793143 completed May 2, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ec45020c8190ac6e21460dbac3d7 completed May 23, 2026, 6:04 p.m.
NEDg Description generation batch_6a11ecf53a20819083a0f23be7d859a4 completed May 23, 2026, 6:07 p.m.
NED2 Entity disambiguation (via description) batch_6a11edae81bc8190aa626f0cd67562d9 completed May 23, 2026, 6:10 p.m.
Created at: April 27, 2026, 2:32 a.m.