Triple

T29036674
Position Surface form Disambiguated ID Type / Status
Subject White Nile State E737879 entity
Predicate partOf P40 FINISHED
Object Greater Nile region
The Greater Nile region is a geographic and cultural area in northeastern Africa encompassing territories along the Nile River, including parts of Sudan such as White Nile State.
E1849237 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: Greater Nile region | Statement: [White Nile State, partOf, Greater Nile region]
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: Greater Nile region
Triple: [White Nile State, partOf, Greater Nile region]
Generated description
The Greater Nile region is a geographic and cultural area in northeastern Africa encompassing territories along the Nile River, including parts of Sudan such as White Nile State.

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_69f077efb3848190b41574e1670f6ae2 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f6603db2988190af8ce0beaaec257d completed May 2, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2537a145648190a6c80dce4914df21 completed June 7, 2026, 9:19 a.m.
NEDg Description generation batch_6a253caf034881909fe3253375748aef completed June 7, 2026, 9:41 a.m.
NED2 Entity disambiguation (via description) batch_6a2540a56bd48190b9b5f3af0d900741 completed June 7, 2026, 9:57 a.m.
Created at: April 28, 2026, 9:59 a.m.