Triple

T25846593
Position Surface form Disambiguated ID Type / Status
Subject Kamrup district E651085 entity
Predicate hasReligiousSite P916 FINISHED
Object Hayagriva Madhava Temple
Hayagriva Madhava Temple is a prominent Hindu shrine in Assam, India, dedicated to Lord Vishnu in his Hayagriva (horse-headed) form and revered as an important pilgrimage site.
E1751648 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: Hayagriva Madhava Temple | Statement: [Kamrup district, hasReligiousSite, Hayagriva Madhava 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: Hayagriva Madhava Temple
Triple: [Kamrup district, hasReligiousSite, Hayagriva Madhava Temple]
Generated description
Hayagriva Madhava Temple is a prominent Hindu shrine in Assam, India, dedicated to Lord Vishnu in his Hayagriva (horse-headed) form and revered as an important pilgrimage site.

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_69e7ab38086081908f3a8e7e0c6efd83 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f6023837c481908c17d2e7f89aeed6 completed May 2, 2026, 1:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12296b269c819095b3684e0ac7735d completed May 23, 2026, 10:25 p.m.
NEDg Description generation batch_6a122d440b188190a9f30a83dde37fd8 completed May 23, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_6a122d9d354481908564d175114e75eb completed May 23, 2026, 10:43 p.m.
Created at: April 22, 2026, 7:53 a.m.