Triple

T24704491
Position Surface form Disambiguated ID Type / Status
Subject Tonga language E611848 entity
Predicate hasStandardizationEffortBy P7791 FINISHED
Object Zambian Ministry of Education
The Zambian Ministry of Education is the government body responsible for formulating and implementing national education policies, curricula, and language-in-education initiatives across Zambia.
E1647628 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: Zambian Ministry of Education | Statement: [Tonga language, hasStandardizationEffortBy, Zambian Ministry of 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: Zambian Ministry of Education
Triple: [Tonga language, hasStandardizationEffortBy, Zambian Ministry of Education]
Generated description
The Zambian Ministry of Education is the government body responsible for formulating and implementing national education policies, curricula, and language-in-education initiatives across Zambia.

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_69e2c4d9c24c8190a3712d74327f0c6e completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f40ff2474c819094f5bc2c9ce7e80b completed May 1, 2026, 2:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10100bfc2c8190a197cdea1521b910 completed May 22, 2026, 8:13 a.m.
NEDg Description generation batch_6a10136b70f4819096d05c3f3fed09c2 completed May 22, 2026, 8:27 a.m.
NED2 Entity disambiguation (via description) batch_6a10145c05c88190a29367197865506c completed May 22, 2026, 8:31 a.m.
Created at: April 18, 2026, 3:23 a.m.