Triple

T6040875
Position Surface form Disambiguated ID Type / Status
Subject 1994 Rwandan genocide E134539 entity
Predicate location P40 FINISHED
Object Gisenyi
Gisenyi is a city in northwestern Rwanda on the shores of Lake Kivu, historically significant as one of the key sites affected during the 1994 Rwandan genocide.
 E573046 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: Gisenyi | Statement: [1994 Rwandan genocide, location, Gisenyi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gisenyi
Context triple: [1994 Rwandan genocide, location, Gisenyi]
  • A. Bukavu
    Bukavu is a major city in the eastern Democratic Republic of the Congo, located on the southwestern shore of Lake Kivu near the Rwandan border.
  • B. Butare
    Butare is a city in southern Rwanda that became a significant site of massacres and atrocities during the 1994 Rwandan genocide.
  • C. Gitega
    Gitega is the political and administrative capital city of Burundi, located in the central part of the country.
  • D. Uvira
    Uvira is a city in the eastern Democratic Republic of the Congo, located on the northern shores of Lake Tanganyika near the border with Burundi.
  • E. Butembo
    Butembo is a major commercial city in eastern Democratic Republic of the Congo, known as a trading hub and economic center in North Kivu.
  • 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: Gisenyi
Triple: [1994 Rwandan genocide, location, Gisenyi]
Generated description
Gisenyi is a city in northwestern Rwanda on the shores of Lake Kivu, historically significant as one of the key sites affected during the 1994 Rwandan genocide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gisenyi
Target entity description: Gisenyi is a city in northwestern Rwanda on the shores of Lake Kivu, historically significant as one of the key sites affected during the 1994 Rwandan genocide.
  • A. Bukavu
    Bukavu is a major city in the eastern Democratic Republic of the Congo, located on the southwestern shore of Lake Kivu near the Rwandan border.
  • B. Butare
    Butare is a city in southern Rwanda that became a significant site of massacres and atrocities during the 1994 Rwandan genocide.
  • C. Gitega
    Gitega is the political and administrative capital city of Burundi, located in the central part of the country.
  • D. Uvira
    Uvira is a city in the eastern Democratic Republic of the Congo, located on the northern shores of Lake Tanganyika near the border with Burundi.
  • E. Butembo
    Butembo is a major commercial city in eastern Democratic Republic of the Congo, known as a trading hub and economic center in North Kivu.
  • 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_69c00875db5c819099dd5bb833ec43c2 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c056cf82d481909d5161fe3643e7ed completed March 22, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c14149f97081908d57c21652097ad3 completed March 23, 2026, 1:34 p.m.
NEDg Description generation batch_69c143417a9881909360412b1ed7be86 completed March 23, 2026, 1:42 p.m.
NED2 Entity disambiguation (via description) batch_69c143c59fe881909ccfd159bfdc753a completed March 23, 2026, 1:44 p.m.
Created at: March 22, 2026, 4:08 p.m.