Triple

T36403133
Position Surface form Disambiguated ID Type / Status
Subject Selangor Club Padang E896682 entity
Predicate near P350 FINISHED
Object Jamek Mosque
Jamek Mosque is one of Kuala Lumpur’s oldest and most historically significant mosques, known for its Moorish architecture and location at the confluence of the Klang and Gombak rivers.
E2188415 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: Jamek Mosque | Statement: [Selangor Club Padang, near, Jamek Mosque]
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: Jamek Mosque
Triple: [Selangor Club Padang, near, Jamek Mosque]
Generated description
Jamek Mosque is one of Kuala Lumpur’s oldest and most historically significant mosques, known for its Moorish architecture and location at the confluence of the Klang and Gombak rivers.

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_69f76e53b81081908d3b81860593f38a completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd16c1a881909acf1d69357eb8ed completed May 3, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39e6c908b08190ac34fafe8663ffe2 completed June 23, 2026, 1:52 a.m.
NEDg Description generation batch_6a39e82896d08190851ad8bb6a793b6a completed June 23, 2026, 1:58 a.m.
NED2 Entity disambiguation (via description) batch_6a39e88d8954819083d2669a9223a0aa completed June 23, 2026, 1:59 a.m.
Created at: May 3, 2026, 4:10 p.m.