Triple

T34109549
Position Surface form Disambiguated ID Type / Status
Subject Bodhi Tataung E874801 entity
Predicate hasStatue P1646 FINISHED
Object Laykyun Sekkya
Laykyun Sekkya is a towering standing Buddha statue in Myanmar, recognized as one of the tallest statues in the world.
E2082293 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: Laykyun Sekkya | Statement: [Bodhi Tataung, hasStatue, Laykyun Sekkya]
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: Laykyun Sekkya
Triple: [Bodhi Tataung, hasStatue, Laykyun Sekkya]
Generated description
Laykyun Sekkya is a towering standing Buddha statue in Myanmar, recognized as one of the tallest statues in the world.

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_69f349a80d4481908527317d43f5c579 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70cb061d8819098510de651f2d59a completed May 3, 2026, 8:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36b7692b188190aadcf52ff42324d3 completed June 20, 2026, 3:53 p.m.
NEDg Description generation batch_6a36b81e1e588190bb400c76f45944d1 completed June 20, 2026, 3:56 p.m.
NED2 Entity disambiguation (via description) batch_6a36b9868250819097430b3864d75880 completed June 20, 2026, 4:02 p.m.
Created at: May 1, 2026, 1:53 a.m.