Triple

T26419092

Position	Surface form	Disambiguated ID	Type / Status
Subject	Nandamuri Harikrishna	`E664183`	entity
Predicate	spouse	`P13`	FINISHED
Object	Shalini Harikrishna Shalini Harikrishna is known as the wife of the late Indian actor and politician Nandamuri Harikrishna, a prominent member of the Nandamuri family in Telugu cinema and politics.	`E1819304`	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: Shalini Harikrishna | Statement: [Nandamuri Harikrishna, spouse, Shalini Harikrishna]

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: Shalini Harikrishna
Triple: [Nandamuri Harikrishna, spouse, Shalini Harikrishna]

Generated description

Shalini Harikrishna is known as the wife of the late Indian actor and politician Nandamuri Harikrishna, a prominent member of the Nandamuri family in Telugu cinema and politics.

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_69ee883a04ec81908883c4559f8c7e24`	completed	April 26, 2026, 9:48 p.m.
NER	Named-entity recognition	`batch_69f6113968208190ba2ea9ac59fbc54d`	completed	May 2, 2026, 2:59 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a164154ce1881908206b07bfcbfe378`	completed	May 27, 2026, 12:56 a.m.
NEDg	Description generation	`batch_6a1642a04a9c81908f196894b8f4bdf5`	completed	May 27, 2026, 1:02 a.m.
NED2	Entity disambiguation (via description)	`batch_6a164322f1148190b37794a5fc54f184`	completed	May 27, 2026, 1:04 a.m.

Created at: April 26, 2026, 11:42 p.m.