Triple

T26791966
Position Surface form Disambiguated ID Type / Status
Subject East West MRT line E670541 entity
Predicate hasTerminus P388 FINISHED
Object Pasir Ris MRT station
Pasir Ris MRT station is an elevated Mass Rapid Transit station in eastern Singapore serving the Pasir Ris residential town as part of the East West Line.
E1822130 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: Pasir Ris MRT station | Statement: [East West MRT line, hasTerminus, Pasir Ris MRT 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: Pasir Ris MRT station
Triple: [East West MRT line, hasTerminus, Pasir Ris MRT station]
Generated description
Pasir Ris MRT station is an elevated Mass Rapid Transit station in eastern Singapore serving the Pasir Ris residential town as part of the East West Line.

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_69eeb31d45f8819089f52ebdbc556218 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f619bbe6a4819090598d7e100c2016 completed May 2, 2026, 3:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cac179f948190ae2d5989bb199d30 completed May 31, 2026, 9:45 p.m.
NEDg Description generation batch_6a1cacd14e048190b6a26e9b5750dff8 completed May 31, 2026, 9:49 p.m.
NED2 Entity disambiguation (via description) batch_6a1cadd09b908190afc24c7665a804c4 completed May 31, 2026, 9:53 p.m.
Created at: April 27, 2026, 4:17 a.m.