Triple

T25714218
Position Surface form Disambiguated ID Type / Status
Subject Riti Yuga of Odia literature E644814 entity
Predicate hasNotablePoet P4290 FINISHED
Object Kavisurya Baladeba Ratha
Kavisurya Baladeba Ratha was a prominent Odia poet renowned for his pioneering contributions to the Riti Yuga (classical age) of Odia literature.
E1700645 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: Kavisurya Baladeba Ratha | Statement: [Riti Yuga of Odia literature, hasNotablePoet, Kavisurya Baladeba Ratha]
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: Kavisurya Baladeba Ratha
Triple: [Riti Yuga of Odia literature, hasNotablePoet, Kavisurya Baladeba Ratha]
Generated description
Kavisurya Baladeba Ratha was a prominent Odia poet renowned for his pioneering contributions to the Riti Yuga (classical age) of Odia literature.

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_69e77e83c8ec8190bf52fcdac4838984 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fc610aac81909ee4722dcfcca67d completed May 2, 2026, 1:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ec97cf6481908d49e5393e3dff28 completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10ee62df94819093fe3a38e8305ee0 completed May 23, 2026, 12:01 a.m.
NED2 Entity disambiguation (via description) batch_6a10ef523db88190804391458feb600d completed May 23, 2026, 12:05 a.m.
Created at: April 21, 2026, 9:23 p.m.