Triple

T28695783
Position Surface form Disambiguated ID Type / Status
Subject Long Vân Pagoda E729412 entity
Predicate partOf P40 FINISHED
Object Perfume Pagoda complex
The Perfume Pagoda complex is a famous Buddhist pilgrimage site in northern Vietnam, consisting of numerous temples and pagodas set amid dramatic limestone mountains and caves.
E1830826 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: Perfume Pagoda complex | Statement: [Long Vân Pagoda, partOf, Perfume Pagoda complex]
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: Perfume Pagoda complex
Triple: [Long Vân Pagoda, partOf, Perfume Pagoda complex]
Generated description
The Perfume Pagoda complex is a famous Buddhist pilgrimage site in northern Vietnam, consisting of numerous temples and pagodas set amid dramatic limestone mountains and caves.

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_69f043e6e9688190b6bdd6e5665498ff completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f656af1dec8190a5ad3298de3cb914 completed May 2, 2026, 7:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1ccf48c6e48190b44516e0b940bb8f completed June 1, 2026, 12:16 a.m.
NEDg Description generation batch_6a1cd020780c81908d33cd9d1676a762 completed June 1, 2026, 12:19 a.m.
NED2 Entity disambiguation (via description) batch_6a2494722c7c8190b67b87014e4a2f0a completed June 6, 2026, 9:43 p.m.
Created at: April 28, 2026, 5:39 a.m.