Triple

T31283699
Position Surface form Disambiguated ID Type / Status
Subject Minister of National Education E797742 entity
Predicate heads P652 FINISHED
Object Ministry of National Education
The Ministry of National Education is a government department responsible for designing, implementing, and overseeing a country's national education policies and school system.
E1957122 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: Ministry of National Education | Statement: [Minister of National Education, heads, Ministry of National Education]
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: Ministry of National Education
Triple: [Minister of National Education, heads, Ministry of National Education]
Generated description
The Ministry of National Education is a government department responsible for designing, implementing, and overseeing a country's national education policies and school system.

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_69f224def9088190a37034eab3daf57f completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69e01d7dc8190b7f4d5fe9427566b completed May 3, 2026, 12:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2a1e2c0e9c81908b83a36b44c7329f completed June 11, 2026, 2:32 a.m.
NEDg Description generation batch_6a2a2db5470081908c094fb8f5b0d047 completed June 11, 2026, 3:38 a.m.
NED2 Entity disambiguation (via description) batch_6a2a2e3def50819084a2a2a1104c061a completed June 11, 2026, 3:40 a.m.
Created at: April 29, 2026, 9:13 p.m.