Triple

T9433185
Position Surface form Disambiguated ID Type / Status
Subject Lualaba River E227434 entity
Predicate majorCityOnRiver P316 FINISHED
Object Likasi
Likasi is a mining city in the southeastern Democratic Republic of the Congo, known for its significant copper and cobalt production.
 E799130 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: Likasi | Statement: [Lualaba River, majorCityOnRiver, Likasi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Likasi
Context triple: [Lualaba River, majorCityOnRiver, Likasi]
  • A. Dar es Salaam
    Dar es Salaam is a major coastal metropolis on the Indian Ocean and the principal economic and commercial hub of Tanzania.
  • B. Dodoma
    Dodoma is the political and administrative capital city of Tanzania, located in the country’s central region.
  • C. Zanzibar City
    Zanzibar City is the historic and administrative capital of Zanzibar, Tanzania, renowned for its UNESCO-listed Stone Town and rich Swahili, Arab, and colonial heritage.
  • D. Nyamwezi
    Nyamwezi is a Bantu language spoken primarily in northwestern Tanzania by the Nyamwezi people.
  • E. Kalangala
    Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
  • 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: Likasi
Triple: [Lualaba River, majorCityOnRiver, Likasi]
Generated description
Likasi is a mining city in the southeastern Democratic Republic of the Congo, known for its significant copper and cobalt production.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Likasi
Target entity description: Likasi is a mining city in the southeastern Democratic Republic of the Congo, known for its significant copper and cobalt production.
  • A. Dar es Salaam
    Dar es Salaam is a major coastal metropolis on the Indian Ocean and the principal economic and commercial hub of Tanzania.
  • B. Dodoma
    Dodoma is the political and administrative capital city of Tanzania, located in the country’s central region.
  • C. Zanzibar City
    Zanzibar City is the historic and administrative capital of Zanzibar, Tanzania, renowned for its UNESCO-listed Stone Town and rich Swahili, Arab, and colonial heritage.
  • D. Nyamwezi
    Nyamwezi is a Bantu language spoken primarily in northwestern Tanzania by the Nyamwezi people.
  • E. Kalangala
    Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
  • 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_69ca8437a7ac81908651de48f2d2141d completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7e61a114819081fc4a2ad39c96ba completed April 1, 2026, 8:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1104514d481908d7cb9a87a01f1e2 completed April 4, 2026, 1:21 p.m.
NEDg Description generation batch_69d1115ed8c48190af02a8ec38c8e2b9 completed April 4, 2026, 1:25 p.m.
NED2 Entity disambiguation (via description) batch_69d111f3190c8190ba2fe5687212da25 completed April 4, 2026, 1:28 p.m.
Created at: March 30, 2026, 7:49 p.m.