Triple

T25553805
Position Surface form Disambiguated ID Type / Status
Subject Hoysaleswara Temple, Halebidu E640512 entity
Predicate near P350 FINISHED
Object Dwarasamudra lake
Dwarasamudra Lake is a historic water reservoir in Halebidu, Karnataka, associated with the former Hoysala capital of Dwarasamudra and its renowned temple complex.
E1687377 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: Dwarasamudra lake | Statement: [Hoysaleswara Temple, Halebidu, near, Dwarasamudra lake]
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: Dwarasamudra lake
Triple: [Hoysaleswara Temple, Halebidu, near, Dwarasamudra lake]
Generated description
Dwarasamudra Lake is a historic water reservoir in Halebidu, Karnataka, associated with the former Hoysala capital of Dwarasamudra and its renowned temple complex.

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_69e75dc101a881909fd33b02174e9768 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f8c831208190a542f90eb092977c completed May 2, 2026, 1:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10b74e73d881909dcdb3c4dac05737 completed May 22, 2026, 8:06 p.m.
NEDg Description generation batch_6a10b82504908190904c1ed84610e0c4 completed May 22, 2026, 8:10 p.m.
NED2 Entity disambiguation (via description) batch_6a10b9606818819094491a74c5922378 completed May 22, 2026, 8:15 p.m.
Created at: April 21, 2026, 3:38 p.m.