Triple

T11254013
Position Surface form Disambiguated ID Type / Status
Subject Benishangul-Gumuz Region E266391 entity
Predicate capital P234 FINISHED
Object Assosa
Assosa is a town in western Ethiopia that serves as the administrative and economic center of the Benishangul-Gumuz Region near the Sudanese border.
 E914522 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: Assosa | Statement: [Benishangul-Gumuz Region, capital, Assosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Assosa
Context triple: [Benishangul-Gumuz Region, capital, Assosa]
  • A. Ovambo
    Ovambo is a Bantu language spoken primarily by the Ovambo people in northern Namibia and southern Angola.
  • B. Butana
    Butana is a semi-arid, historically significant region in eastern Sudan, known for its ancient archaeological sites and pastoralist communities.
  • C. Lusiana
    Lusiana is a small town in the Veneto region of northern Italy, known as the birthplace of Indian politician Sonia Gandhi.
  • D. Omaruru
    Omaruru is a small historic town in central Namibia known for its colonial-era architecture, vineyards, and role as a local trading and farming center.
  • E. Anseba
    Anseba is a central region of Eritrea known for its diverse ethnic communities, agriculture, and the regional capital Keren.
  • 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: Assosa
Triple: [Benishangul-Gumuz Region, capital, Assosa]
Generated description
Assosa is a town in western Ethiopia that serves as the administrative and economic center of the Benishangul-Gumuz Region near the Sudanese border.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Assosa
Target entity description: Assosa is a town in western Ethiopia that serves as the administrative and economic center of the Benishangul-Gumuz Region near the Sudanese border.
  • A. Ovambo
    Ovambo is a Bantu language spoken primarily by the Ovambo people in northern Namibia and southern Angola.
  • B. Butana
    Butana is a semi-arid, historically significant region in eastern Sudan, known for its ancient archaeological sites and pastoralist communities.
  • C. Lusiana
    Lusiana is a small town in the Veneto region of northern Italy, known as the birthplace of Indian politician Sonia Gandhi.
  • D. Omaruru
    Omaruru is a small historic town in central Namibia known for its colonial-era architecture, vineyards, and role as a local trading and farming center.
  • E. Anseba
    Anseba is a central region of Eritrea known for its diverse ethnic communities, agriculture, and the regional capital Keren.
  • 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_69d6aac7953c8190b82caf9d7640fdf9 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9346f4c8190b29c2cf3a29cd1d1 completed April 9, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4cc941d34819099ae30713bdd03e5 completed April 19, 2026, 12:37 p.m.
NEDg Description generation batch_69e4d9ec9964819084bd7118e49c41a2 completed April 19, 2026, 1:34 p.m.
NED2 Entity disambiguation (via description) batch_69e4ddab4ef48190ab7f371da765c6c0 completed April 19, 2026, 1:50 p.m.
Created at: April 8, 2026, 9:31 p.m.