Triple

T30924812
Position Surface form Disambiguated ID Type / Status
Subject Sudan People’s Liberation Movement-in-Opposition E787827 entity
Predicate hasDeputyLeader P147 FINISHED
Object Taban Deng Gai
Taban Deng Gai is a South Sudanese politician who has served as a prominent leader in the country’s opposition and as First Vice President of South Sudan.
E1937680 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: Taban Deng Gai | Statement: [Sudan People’s Liberation Movement-in-Opposition, hasDeputyLeader, Taban Deng Gai]
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: Taban Deng Gai
Triple: [Sudan People’s Liberation Movement-in-Opposition, hasDeputyLeader, Taban Deng Gai]
Generated description
Taban Deng Gai is a South Sudanese politician who has served as a prominent leader in the country’s opposition and as First Vice President of South Sudan.

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_69f224bfaca88190b9d0dfcc86297fe9 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f692b82df881909350359a39daa9ff completed May 3, 2026, 12:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28e46b4f4c81908eb3788972bbde88 completed June 10, 2026, 4:13 a.m.
NEDg Description generation batch_6a28e53bedfc8190b0e66f481b11a095 completed June 10, 2026, 4:17 a.m.
NED2 Entity disambiguation (via description) batch_6a28e5c57ebc8190ad3489b51d221021 completed June 10, 2026, 4:19 a.m.
Created at: April 29, 2026, 8:51 p.m.