Triple

T27092436
Position Surface form Disambiguated ID Type / Status
Subject Nepal Police E686203 entity
Predicate hasSpecialUnit P1198 FINISHED
Object Central Investigation Bureau
The Central Investigation Bureau is a specialized investigative unit of the Nepal Police responsible for handling complex, organized, and high-profile criminal cases across the country.
E1756013 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: Central Investigation Bureau | Statement: [Nepal Police, hasSpecialUnit, Central Investigation Bureau]
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: Central Investigation Bureau
Triple: [Nepal Police, hasSpecialUnit, Central Investigation Bureau]
Generated description
The Central Investigation Bureau is a specialized investigative unit of the Nepal Police responsible for handling complex, organized, and high-profile criminal cases across the country.

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_69ef148940ec819097b5c20fbfbf7c81 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f6234a6170819094a1f6d3a7864900 completed May 2, 2026, 4:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a124801cea08190a291fe265755f461 completed May 24, 2026, 12:36 a.m.
NEDg Description generation batch_6a12489d7498819083fb008e2acff886 completed May 24, 2026, 12:38 a.m.
NED2 Entity disambiguation (via description) batch_6a124918ab688190b6172f571d3aba73 completed May 24, 2026, 12:40 a.m.
Created at: April 27, 2026, 8:41 a.m.