Triple

T29328126
Position Surface form Disambiguated ID Type / Status
Subject Democratic Party of Kenya E743706 entity
Predicate hasYouthWing P1088 FINISHED
Object Democratic Party Youth League
The Democratic Party Youth League is the youth wing of Kenya’s Democratic Party, engaging young people in the party’s political activities and leadership development.
E1861937 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: Democratic Party Youth League | Statement: [Democratic Party of Kenya, hasYouthWing, Democratic Party Youth League]
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: Democratic Party Youth League
Triple: [Democratic Party of Kenya, hasYouthWing, Democratic Party Youth League]
Generated description
The Democratic Party Youth League is the youth wing of Kenya’s Democratic Party, engaging young people in the party’s political activities and leadership development.

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_69f09125f784819080f4e9fce9fe624f completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f6689782388190a36b98ec2d60d63f completed May 2, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25a877456c819090d5acdb22578033 completed June 7, 2026, 5:20 p.m.
NEDg Description generation batch_6a25acb956e0819081699c2a218afbc8 completed June 7, 2026, 5:39 p.m.
NED2 Entity disambiguation (via description) batch_6a25b146e9d0819086b956ae8ea30aab completed June 7, 2026, 5:58 p.m.
Created at: April 28, 2026, 1:28 p.m.