Triple

T26949982
Position Surface form Disambiguated ID Type / Status
Subject Lotus Lantern Festival E678754 entity
Predicate alsoKnownAs P39 FINISHED
Object Yeon Deung Hoe
Yeon Deung Hoe is a traditional Korean Buddhist lantern festival, celebrated with colorful parades and illuminated lanterns to honor the birth of the Buddha.
E1780201 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: Yeon Deung Hoe | Statement: [Lotus Lantern Festival, alsoKnownAs, Yeon Deung Hoe]
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: Yeon Deung Hoe
Triple: [Lotus Lantern Festival, alsoKnownAs, Yeon Deung Hoe]
Generated description
Yeon Deung Hoe is a traditional Korean Buddhist lantern festival, celebrated with colorful parades and illuminated lanterns to honor the birth of the Buddha.

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_69eeeb4e75f08190b14fc91ca4a91488 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f6208934108190b9ae04c0ed2c4dde completed May 2, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12d0afe870819099133b53a76f880e completed May 24, 2026, 10:19 a.m.
NEDg Description generation batch_6a12d169e8888190bf3c8e7f0718a3a5 completed May 24, 2026, 10:22 a.m.
NED2 Entity disambiguation (via description) batch_6a12d2747f6881909aa2a5b0c389a494 completed May 24, 2026, 10:27 a.m.
Created at: April 27, 2026, 6:24 a.m.