Triple

T33584150
Position Surface form Disambiguated ID Type / Status
Subject Sujatha Mohan E860233 entity
Predicate alsoKnownAs P39 FINISHED
Object Sujatha
Sujatha is a renowned Indian playback singer celebrated for her extensive work in South Indian cinema, particularly in Malayalam and Tamil films.
E2063862 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: Sujatha | Statement: [Sujatha Mohan, alsoKnownAs, Sujatha]
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: Sujatha
Triple: [Sujatha Mohan, alsoKnownAs, Sujatha]
Generated description
Sujatha is a renowned Indian playback singer celebrated for her extensive work in South Indian cinema, particularly in Malayalam and Tamil films.

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_69f3497e70e48190951c94d072879bec completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f772d24481908f88edf9b7c0a9e7 completed May 3, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a363c7f5ce4819091c441f123121517 completed June 20, 2026, 7:08 a.m.
NEDg Description generation batch_6a3647ea72248190b36e7264d8e83cc6 completed June 20, 2026, 7:57 a.m.
NED2 Entity disambiguation (via description) batch_6a364e53b38881908487bb89b9687ed7 completed June 20, 2026, 8:24 a.m.
Created at: May 1, 2026, 1:40 a.m.