Triple

T26977380
Position Surface form Disambiguated ID Type / Status
Subject royal court of Sri Krishnadevaraya E679494 entity
Predicate hasMember P10 FINISHED
Object Saluva Timmarusu
Saluva Timmarusu was a prominent statesman and prime minister of the Vijayanagara Empire, renowned as the chief advisor and mentor of Emperor Krishnadevaraya.
E1821102 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: Saluva Timmarusu | Statement: [royal court of Sri Krishnadevaraya, hasMember, Saluva Timmarusu]
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: Saluva Timmarusu
Triple: [royal court of Sri Krishnadevaraya, hasMember, Saluva Timmarusu]
Generated description
Saluva Timmarusu was a prominent statesman and prime minister of the Vijayanagara Empire, renowned as the chief advisor and mentor of Emperor Krishnadevaraya.

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_69eeeb507a7081909d516e1fa08b7d29 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f621537bfc8190b006eb8da71c2161 completed May 2, 2026, 4:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cac196b4881908293bfa44977f3b7 completed May 31, 2026, 9:46 p.m.
NEDg Description generation batch_6a1cac9b7c088190972eb6d682ce1c73 completed May 31, 2026, 9:48 p.m.
NED2 Entity disambiguation (via description) batch_6a1cad27e5e48190b2f917c1a51965e0 completed May 31, 2026, 9:50 p.m.
Created at: April 27, 2026, 6:43 a.m.