Triple

T26791992
Position Surface form Disambiguated ID Type / Status
Subject East West MRT line E670541 entity
Predicate hasStation P35 FINISHED
Object Paya Lebar MRT station
Paya Lebar MRT station is a major elevated and underground interchange station in Singapore connecting the East West Line with the Circle Line, serving the Paya Lebar commercial and residential area.
 E1836569 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: Paya Lebar MRT station | Statement: [East West MRT line, hasStation, Paya Lebar 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: Paya Lebar MRT station
Triple: [East West MRT line, hasStation, Paya Lebar MRT station]
Generated description
Paya Lebar MRT station is a major elevated and underground interchange station in Singapore connecting the East West Line with the Circle Line, serving the Paya Lebar commercial and residential area.

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_6a24bb731c0481909aa3925e209c2198 completed June 7, 2026, 12:29 a.m.
NEDg Description generation batch_6a24bfb0987c819089a6705bb5282c4e completed June 7, 2026, 12:47 a.m.
NED2 Entity disambiguation (via description) batch_6a24c54a5d648190b33935999d8f5f04 completed June 7, 2026, 1:11 a.m.
Created at: April 27, 2026, 4:17 a.m.