Triple

T25490134
Position Surface form Disambiguated ID Type / Status
Subject Chennakesava Temple, Belur E638815 entity
Predicate alsoKnownAs P39 FINISHED
Object Chenna Kesava Temple
Chenna Kesava Temple is a renowned 12th-century Hoysala Hindu temple at Belur in Karnataka, India, celebrated for its intricate stone carvings and exemplary Dravidian-Hoysala architecture.
E1682898 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: Chenna Kesava Temple | Statement: [Chennakesava Temple, Belur, alsoKnownAs, Chenna Kesava 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: Chenna Kesava Temple
Triple: [Chennakesava Temple, Belur, alsoKnownAs, Chenna Kesava Temple]
Generated description
Chenna Kesava Temple is a renowned 12th-century Hoysala Hindu temple at Belur in Karnataka, India, celebrated for its intricate stone carvings and exemplary Dravidian-Hoysala architecture.

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_69e75dbbd2a88190b70e1e645de14b9a completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f7a4658081908758aa293923090d completed May 2, 2026, 1:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ad6dc00081909c613de143b0b372 completed May 22, 2026, 7:24 p.m.
NEDg Description generation batch_6a10ae2f577481909be995d38010dcf7 completed May 22, 2026, 7:27 p.m.
NED2 Entity disambiguation (via description) batch_6a10aef10de8819099e12e65f4f9e768 completed May 22, 2026, 7:30 p.m.
Created at: April 21, 2026, 2:38 p.m.