Triple

T33245585
Position Surface form Disambiguated ID Type / Status
Subject Shankar Mahadevan E851088 entity
Predicate spouse P13 FINISHED
Object Sangeeta Mahadevan
Sangeeta Mahadevan is the wife of renowned Indian singer and composer Shankar Mahadevan and is known for largely maintaining a private life away from the public spotlight.
E2044654 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: Sangeeta Mahadevan | Statement: [Shankar Mahadevan, spouse, Sangeeta Mahadevan]
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: Sangeeta Mahadevan
Triple: [Shankar Mahadevan, spouse, Sangeeta Mahadevan]
Generated description
Sangeeta Mahadevan is the wife of renowned Indian singer and composer Shankar Mahadevan and is known for largely maintaining a private life away from the public spotlight.

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_69f34962386c81909ddc3bf9e18ddeb8 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6daf3963081909fc96cbd1642cd21 completed May 3, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35430d5df081909a3aa0f8d1dee1f7 completed June 19, 2026, 1:24 p.m.
NEDg Description generation batch_6a3543fd83a88190b300672a104d9ce4 completed June 19, 2026, 1:28 p.m.
NED2 Entity disambiguation (via description) batch_6a3544cd2b448190aad907008bda0dcb completed June 19, 2026, 1:31 p.m.
Created at: May 1, 2026, 1:31 a.m.