Triple

T25900309
Position Surface form Disambiguated ID Type / Status
Subject Ravindra Kishore Sinha E652594 entity
Predicate founderOf P104 FINISHED
Object Security and Intelligence Services
Security and Intelligence Services is a major Indian private security and facility management company providing guarding, cash logistics, and related services across multiple sectors.
 E1699933 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: Security and Intelligence Services | Statement: [Ravindra Kishore Sinha, founderOf, Security and Intelligence Services]
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: Security and Intelligence Services
Triple: [Ravindra Kishore Sinha, founderOf, Security and Intelligence Services]
Generated description
Security and Intelligence Services is a major Indian private security and facility management company providing guarding, cash logistics, and related services across multiple sectors.

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_69e7ab3c6cc081908de59bfcc28ec19d completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f6038843c481909a71270b5846ba65 completed May 2, 2026, 2 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecc4459881908a9612e7ce1bd1aa completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10ef215b448190853f97729867b5fb completed May 23, 2026, 12:04 a.m.
NED2 Entity disambiguation (via description) batch_6a10efc6a0e48190a595a5025ad5c926 completed May 23, 2026, 12:07 a.m.
Created at: April 22, 2026, 8:24 a.m.