Triple

T27458688
Position Surface form Disambiguated ID Type / Status
Subject BR-10 E692671 entity
Predicate administeredBy P86 FINISHED
Object Regional Transport Office Bhagalpur
Regional Transport Office Bhagalpur is the government agency responsible for vehicle registration, driver licensing, and transport regulation in the Bhagalpur region of Bihar, India.
E1773394 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: Regional Transport Office Bhagalpur | Statement: [BR-10, administeredBy, Regional Transport Office Bhagalpur]
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: Regional Transport Office Bhagalpur
Triple: [BR-10, administeredBy, Regional Transport Office Bhagalpur]
Generated description
Regional Transport Office Bhagalpur is the government agency responsible for vehicle registration, driver licensing, and transport regulation in the Bhagalpur region of Bihar, India.

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_69ef5207903881909427745cda05d27a completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62dcb69848190a512b1bf1fc9a5c7 completed May 2, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b265070c81909a92a6d644bce0d0 completed May 24, 2026, 8:10 a.m.
NEDg Description generation batch_6a12b379225c8190aca2d280575a3f7a completed May 24, 2026, 8:14 a.m.
NED2 Entity disambiguation (via description) batch_6a12b44191688190899b55266e559ede completed May 24, 2026, 8:18 a.m.
Created at: April 27, 2026, 12:49 p.m.