Triple

T24522510
Position Surface form Disambiguated ID Type / Status
Subject Bich Dong caves E606571 entity
Predicate hasPart P35 FINISHED
Object Trung Pagoda
Trung Pagoda is one of the main temple structures within the scenic Bich Dong cave complex in Ninh Binh, Vietnam, known for its historic Buddhist architecture set against a limestone mountain backdrop.
E1662042 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: Trung Pagoda | Statement: [Bich Dong caves, hasPart, Trung Pagoda]
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: Trung Pagoda
Triple: [Bich Dong caves, hasPart, Trung Pagoda]
Generated description
Trung Pagoda is one of the main temple structures within the scenic Bich Dong cave complex in Ninh Binh, Vietnam, known for its historic Buddhist architecture set against a limestone mountain backdrop.

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_69e2c4c85778819085f5da9af3569ad5 completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a872c120819095c9d50722230d66 completed April 30, 2026, 12:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10487199ac819089cde078a1fa0811 completed May 22, 2026, 12:13 p.m.
NEDg Description generation batch_6a10498ee91081909f400a590f3646a7 completed May 22, 2026, 12:18 p.m.
NED2 Entity disambiguation (via description) batch_6a104aa15f248190ba69524b7d516bc1 completed May 22, 2026, 12:22 p.m.
Created at: April 18, 2026, 2:25 a.m.