Triple

T26955063
Position Surface form Disambiguated ID Type / Status
Subject Commissioner of the African Union E678876 entity
Predicate hasPortfolioExamples P46877 FINISHED
Object Trade and Industry
Trade and Industry is the African Union policy portfolio responsible for promoting intra-African trade, industrial development, and economic integration across member states.
E1750333 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: Trade and Industry | Statement: [Commissioner of the African Union, hasPortfolioExamples, Trade and Industry]
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: Trade and Industry
Triple: [Commissioner of the African Union, hasPortfolioExamples, Trade and Industry]
Generated description
Trade and Industry is the African Union policy portfolio responsible for promoting intra-African trade, industrial development, and economic integration across member states.

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_69eeeb4e75f08190b14fc91ca4a91488 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f79109f3b081909cabb6fcce56ac7b completed May 3, 2026, 6:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12299b3f088190b69ad30d47afd7e9 completed May 23, 2026, 10:26 p.m.
NEDg Description generation batch_6a122a9dabb081908ed47a5d4624d9c6 completed May 23, 2026, 10:30 p.m.
NED2 Entity disambiguation (via description) batch_6a122b4cd8ac8190b23c0ef69951fe05 completed May 23, 2026, 10:33 p.m.
Created at: April 27, 2026, 6:27 a.m.