Triple

T36443106
Position Surface form Disambiguated ID Type / Status
Subject Brickfields E897791 entity
Predicate hasLandmark P105 FINISHED
Object Temple of Fine Arts Kuala Lumpur
The Temple of Fine Arts Kuala Lumpur is a renowned cultural and performing arts center dedicated to promoting Indian classical music, dance, and arts in Malaysia.
E2184268 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: Temple of Fine Arts Kuala Lumpur | Statement: [Brickfields, hasLandmark, Temple of Fine Arts Kuala Lumpur]
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: Temple of Fine Arts Kuala Lumpur
Triple: [Brickfields, hasLandmark, Temple of Fine Arts Kuala Lumpur]
Generated description
The Temple of Fine Arts Kuala Lumpur is a renowned cultural and performing arts center dedicated to promoting Indian classical music, dance, and arts in Malaysia.

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_69f76e5720b481908f8177ac24a7560b completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd89a94c8190b6349901c54a1cff completed May 3, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39c41cb38881909d30155ac6c93ee7 completed June 22, 2026, 11:24 p.m.
NEDg Description generation batch_6a39c5d09e008190a8f0114c85a30a9b completed June 22, 2026, 11:31 p.m.
NED2 Entity disambiguation (via description) batch_6a39c8408e988190929af379e9b71291 completed June 22, 2026, 11:41 p.m.
Created at: May 3, 2026, 4:10 p.m.