Triple

T25256183
Position Surface form Disambiguated ID Type / Status
Subject Sri Sri E633179 entity
Predicate fullName P16 FINISHED
Object Srirangam Srinivasa Rao
Srirangam Srinivasa Rao, popularly known as Sri Sri, was a pioneering 20th-century Telugu poet and lyricist celebrated for introducing modernist and progressive themes into Telugu literature.
E1861704 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: Srirangam Srinivasa Rao | Statement: [Sri Sri, fullName, Srirangam Srinivasa Rao]
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: Srirangam Srinivasa Rao
Triple: [Sri Sri, fullName, Srirangam Srinivasa Rao]
Generated description
Srirangam Srinivasa Rao, popularly known as Sri Sri, was a pioneering 20th-century Telugu poet and lyricist celebrated for introducing modernist and progressive themes into Telugu 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_69e75a922ad481908f4f1f884583cb42 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f4838d5a7881908b8bfd03cf6f51b6 completed May 1, 2026, 10:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a25a829d6b08190af6c336fdd7f38c8 completed June 7, 2026, 5:19 p.m.
NEDg Description generation batch_6a25aca216088190b6e106c9172f638c completed June 7, 2026, 5:38 p.m.
NED2 Entity disambiguation (via description) batch_6a25b146e9d0819086b956ae8ea30aab completed June 7, 2026, 5:58 p.m.
Created at: April 21, 2026, 1:13 p.m.