Triple

T25816462
Position Surface form Disambiguated ID Type / Status
Subject Adhar Devi Temple E650268 entity
Predicate alsoKnownAs P39 FINISHED
Object Arbuda Devi Temple
Arbuda Devi Temple is a revered Hindu shrine dedicated to the goddess Durga, located in a cave on Mount Abu in Rajasthan, India, and is a popular pilgrimage and tourist destination.
E1741103 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: Arbuda Devi Temple | Statement: [Adhar Devi Temple, alsoKnownAs, Arbuda Devi Temple]
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: Arbuda Devi Temple
Triple: [Adhar Devi Temple, alsoKnownAs, Arbuda Devi Temple]
Generated description
Arbuda Devi Temple is a revered Hindu shrine dedicated to the goddess Durga, located in a cave on Mount Abu in Rajasthan, India, and is a popular pilgrimage and tourist destination.

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_69e7ab367fcc8190a5ff1e7f3da046a4 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f600c915908190aea4b20f6b9b11b6 completed May 2, 2026, 1:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a120915df4c819095496676b27bdc33 completed May 23, 2026, 8:07 p.m.
NEDg Description generation batch_6a120a567424819083cc2364aa6ec9da completed May 23, 2026, 8:13 p.m.
NED2 Entity disambiguation (via description) batch_6a120b5561cc81909195b6d74ec74b50 completed May 23, 2026, 8:17 p.m.
Created at: April 22, 2026, 7:26 a.m.