Triple

T3117303
Position Surface form Disambiguated ID Type / Status
Subject Lake Kyoga E65092 entity
Predicate nearCity P350 FINISHED
Object Nakasongola
Nakasongola is a town in central Uganda that serves as an administrative and commercial center for the surrounding rural district.
 E338918 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: Nakasongola | Statement: [Lake Kyoga, nearCity, Nakasongola]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nakasongola
Context triple: [Lake Kyoga, nearCity, Nakasongola]
  • A. Monguno
    Monguno is a town and local government area in Borno State, northeastern Nigeria, known for its strategic location and role in regional security dynamics.
  • B. Kanyaga
    "Kanyaga" is a popular Tanzanian Bongo Flava hit song by Diamond Platnumz known for its energetic beat and danceable style.
  • C. Mbagala
    "Mbagala" is a popular hit song by Tanzanian Bongo Flava artist Diamond Platnumz that helped establish his early fame in East Africa.
  • D. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • E. Lusoga
    Lusoga is a Bantu language spoken primarily by the Basoga people in eastern Uganda.
  • 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: Nakasongola
Triple: [Lake Kyoga, nearCity, Nakasongola]
Generated description
Nakasongola is a town in central Uganda that serves as an administrative and commercial center for the surrounding rural district.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nakasongola
Target entity description: Nakasongola is a town in central Uganda that serves as an administrative and commercial center for the surrounding rural district.
  • A. Monguno
    Monguno is a town and local government area in Borno State, northeastern Nigeria, known for its strategic location and role in regional security dynamics.
  • B. Kanyaga
    "Kanyaga" is a popular Tanzanian Bongo Flava hit song by Diamond Platnumz known for its energetic beat and danceable style.
  • C. Mbagala
    "Mbagala" is a popular hit song by Tanzanian Bongo Flava artist Diamond Platnumz that helped establish his early fame in East Africa.
  • D. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • E. Lusoga
    Lusoga is a Bantu language spoken primarily by the Basoga people in eastern Uganda.
  • 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_69ad857fcc088190b0c4d45a5cde6f61 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada4e73cc88190846ef37ccf1a0de7 completed March 8, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b276e63ce481908671453ca67586f1 completed March 12, 2026, 8:18 a.m.
NEDg Description generation batch_69b277c9faa48190b15c5ca0ec8625a0 completed March 12, 2026, 8:22 a.m.
NED2 Entity disambiguation (via description) batch_69b2781855ec819089fbe4fd874115a2 completed March 12, 2026, 8:23 a.m.
Created at: March 8, 2026, 3:04 p.m.