Triple

T26893050
Position Surface form Disambiguated ID Type / Status
Subject cadet college system of Bangladesh E677825 entity
Predicate hasComponent P35 FINISHED
Object Barisal Cadet College
Barisal Cadet College is a residential military-style secondary school in Bangladesh that prepares selected students for leadership roles and potential careers in the armed forces.
E1762026 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: Barisal Cadet College | Statement: [cadet college system of Bangladesh, hasComponent, Barisal Cadet College]
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: Barisal Cadet College
Triple: [cadet college system of Bangladesh, hasComponent, Barisal Cadet College]
Generated description
Barisal Cadet College is a residential military-style secondary school in Bangladesh that prepares selected students for leadership roles and potential careers in the armed forces.

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_69eee9befee48190a26f214faa867be7 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61f69e4508190ab20c3f2052282e7 completed May 2, 2026, 3:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a125362ce088190a4ab16355b72f113 completed May 24, 2026, 1:24 a.m.
NEDg Description generation batch_6a12545544f881909f0afd8459986559 completed May 24, 2026, 1:28 a.m.
NED2 Entity disambiguation (via description) batch_6a125879112c8190959380eaef8ccf19 completed May 24, 2026, 1:46 a.m.
Created at: April 27, 2026, 5:46 a.m.