Triple

T28433190
Position Surface form Disambiguated ID Type / Status
Subject Ballari district E715191 entity
Predicate hasReligiousSite P916 FINISHED
Object Mylara Lingeshwara Temple
Mylara Lingeshwara Temple is a prominent Hindu pilgrimage center in Karnataka dedicated to Lord Shiva, renowned for its annual fair and regional cultural significance.
E1886787 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: Mylara Lingeshwara Temple | Statement: [Ballari district, hasReligiousSite, Mylara Lingeshwara 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: Mylara Lingeshwara Temple
Triple: [Ballari district, hasReligiousSite, Mylara Lingeshwara Temple]
Generated description
Mylara Lingeshwara Temple is a prominent Hindu pilgrimage center in Karnataka dedicated to Lord Shiva, renowned for its annual fair and regional cultural significance.

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_69efd6b253888190b3c7222ed6a403a8 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f64e0256b88190b31b2ce77b4c772c completed May 2, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26e5c9603c8190bd5f66270cc99533 completed June 8, 2026, 3:54 p.m.
NEDg Description generation batch_6a26e9993aa48190afc523933c4e0f85 completed June 8, 2026, 4:11 p.m.
NED2 Entity disambiguation (via description) batch_6a26ea0a856881909d0cfea0f1fa94ec completed June 8, 2026, 4:12 p.m.
Created at: April 28, 2026, 1:41 a.m.