Triple

T27724758
Position Surface form Disambiguated ID Type / Status
Subject Revati E699063 entity
Predicate father P120 FINISHED
Object Kakudmi
Kakudmi is a king in Hindu mythology known as the father of Revati and for traveling to Brahma’s realm, returning to find that ages had passed on Earth.
E1786346 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: Kakudmi | Statement: [Revati, father, Kakudmi]
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: Kakudmi
Triple: [Revati, father, Kakudmi]
Generated description
Kakudmi is a king in Hindu mythology known as the father of Revati and for traveling to Brahma’s realm, returning to find that ages had passed on Earth.

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_69ef591012dc8190a6f1ec994f9f7ff7 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f6363f74248190966df10d3445b5ea completed May 2, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e46cc3ec81908200e9cb6f4bb895 completed May 24, 2026, 11:43 a.m.
NEDg Description generation batch_6a12e4fca4088190b20187243cbf974e completed May 24, 2026, 11:46 a.m.
NED2 Entity disambiguation (via description) batch_6a12e606bc688190958b5e84777566fb completed May 24, 2026, 11:50 a.m.
Created at: April 27, 2026, 3:08 p.m.