Triple

T36499251
Position Surface form Disambiguated ID Type / Status
Subject Dang Wangi station E899276 entity
Predicate connectedTo P37 FINISHED
Object Bukit Nanas Monorail station
Bukit Nanas Monorail station is an elevated Kuala Lumpur Monorail stop located near the city center, serving the Bukit Nanas area and providing convenient access to nearby commercial and tourist attractions.
E2202415 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: Bukit Nanas Monorail station | Statement: [Dang Wangi station, connectedTo, Bukit Nanas Monorail station]
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: Bukit Nanas Monorail station
Triple: [Dang Wangi station, connectedTo, Bukit Nanas Monorail station]
Generated description
Bukit Nanas Monorail station is an elevated Kuala Lumpur Monorail stop located near the city center, serving the Bukit Nanas area and providing convenient access to nearby commercial and tourist attractions.

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_69f76e5b92088190933afda3f7531dd4 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c1c1e4d88190bce8e5a4ef6dcc8d completed May 3, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dfac0091081909d481f105ed758b4 completed June 26, 2026, 4:06 a.m.
NEDg Description generation batch_6a3dfe292b788190a6316cc67c5ce0bc completed June 26, 2026, 4:20 a.m.
NED2 Entity disambiguation (via description) batch_6a3e03327fe481908577744b1addfa8a completed June 26, 2026, 4:42 a.m.
Created at: May 3, 2026, 4:10 p.m.