Triple

T36620429
Position Surface form Disambiguated ID Type / Status
Subject Sea of Gazelles E904020 entity
Predicate administrativelyDividedInto P44156 FINISHED
Object Northern Bahr el Ghazal State
Northern Bahr el Ghazal State is a region in northwestern South Sudan known for its rural communities, floodplains, and proximity to the border with Sudan.
 E2208386 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: Northern Bahr el Ghazal State | Statement: [Sea of Gazelles, administrativelyDividedInto, Northern Bahr el Ghazal State]
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: Northern Bahr el Ghazal State
Triple: [Sea of Gazelles, administrativelyDividedInto, Northern Bahr el Ghazal State]
Generated description
Northern Bahr el Ghazal State is a region in northwestern South Sudan known for its rural communities, floodplains, and proximity to the border with 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_69f76e6ae750819096911e6e2d4d12c5 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c48447fc81909c73dfa3b780b40b completed May 3, 2026, 9:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e5742f7508190b46165c2ce0f3f55 completed June 26, 2026, 10:41 a.m.
NEDg Description generation batch_6a3e5861b2b48190b5958130724324d1 completed June 26, 2026, 10:45 a.m.
NED2 Entity disambiguation (via description) batch_6a3e5f7deea0819096307262cf2134a4 completed June 26, 2026, 11:16 a.m.
Created at: May 3, 2026, 4:11 p.m.