Triple

T1184815
Position Surface form Disambiguated ID Type / Status
Subject Nubia E25220 entity
Predicate hasCity P316 FINISHED
Object Dongola
Dongola is a historic town in northern Sudan that served as a major political and cultural center of medieval Nubian kingdoms along the Nile.
E138678 NE FINISHED

How this triple was built (4 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: Dongola | Statement: [Nubia, hasCity, Dongola]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dongola
Context triple: [Nubia, hasCity, Dongola]
  • A. Omdurman
    Omdurman is a major city in Sudan, historically significant as a cultural and commercial center and effectively forming part of the country’s greater capital area.
  • B. Gash‑Barka
    Gash‑Barka is a largely agricultural region in southwestern Eritrea known for its fertile land and role as one of the country’s main food-producing areas.
  • C. Aswan
    Aswan is a historic city in southern Egypt on the Nile River, known for its ancient temples, quarries, and the nearby Aswan High Dam.
  • D. Port Sudan
    Port Sudan is Sudan’s main seaport on the Red Sea, serving as the country’s primary hub for maritime trade and transport.
  • E. Juba
    Juba is the capital and largest city of South Sudan, serving as its political, economic, and administrative center.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Dongola
Triple: [Nubia, hasCity, Dongola]
Generated description
Dongola is a historic town in northern Sudan that served as a major political and cultural center of medieval Nubian kingdoms along the Nile.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dongola
Target entity description: Dongola is a historic town in northern Sudan that served as a major political and cultural center of medieval Nubian kingdoms along the Nile.
  • A. Omdurman
    Omdurman is a major city in Sudan, historically significant as a cultural and commercial center and effectively forming part of the country’s greater capital area.
  • B. Gash‑Barka
    Gash‑Barka is a largely agricultural region in southwestern Eritrea known for its fertile land and role as one of the country’s main food-producing areas.
  • C. Aswan
    Aswan is a historic city in southern Egypt on the Nile River, known for its ancient temples, quarries, and the nearby Aswan High Dam.
  • D. Port Sudan
    Port Sudan is Sudan’s main seaport on the Red Sea, serving as the country’s primary hub for maritime trade and transport.
  • E. Juba
    Juba is the capital and largest city of South Sudan, serving as its political, economic, and administrative center.
  • F. None of above. chosen

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_69a49427d98881908646d6c63b8cea1e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd39245881908766c41943dc2752 completed March 1, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7f3443588190af6c06383e904e7d completed March 7, 2026, 7:40 p.m.
NEDg Description generation batch_69ac7fba00f0819086a0fffa090c5809 completed March 7, 2026, 7:42 p.m.
NED2 Entity disambiguation (via description) batch_69ac807ead9c819088f7195aec87a538 completed March 7, 2026, 7:46 p.m.
Created at: March 1, 2026, 7:45 p.m.