Triple

T29615309
Position Surface form Disambiguated ID Type / Status
Subject Jayaprada E754844 entity
Predicate spouse P13 FINISHED
Object Srikant Nahata
Srikant Nahata is an Indian film producer known for his work in Hindi and regional cinema and for his marriage to actress Jayaprada.
E1927507 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: Srikant Nahata | Statement: [Jayaprada, spouse, Srikant Nahata]
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: Srikant Nahata
Triple: [Jayaprada, spouse, Srikant Nahata]
Generated description
Srikant Nahata is an Indian film producer known for his work in Hindi and regional cinema and for his marriage to actress Jayaprada.

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_69f0ef85f62081909842b59fdf8717e1 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f66e20cefc8190aacd49631e0c5274 completed May 2, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2898b600448190a3eb0a50fff3fbbc completed June 9, 2026, 10:50 p.m.
NEDg Description generation batch_6a28994a88ec8190a0d674c7a45685d8 completed June 9, 2026, 10:52 p.m.
NED2 Entity disambiguation (via description) batch_6a2899d7d0e48190b7bf380a413e5598 completed June 9, 2026, 10:55 p.m.
Created at: April 28, 2026, 6:31 p.m.