Triple

T7854120
Position Surface form Disambiguated ID Type / Status
Subject Bantu E languages E182127 entity
Predicate hasMember P10 FINISHED
Object Rukiga
Rukiga is a Bantu language spoken primarily by the Bakiga people in southwestern Uganda.
 E705636 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: Rukiga | Statement: [Bantu E languages, hasMember, Rukiga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rukiga
Context triple: [Bantu E languages, hasMember, Rukiga]
  • A. Kisoro
    Kisoro is a small town in southwestern Uganda known as a gateway to gorilla trekking and the nearby Bwindi Impenetrable and Mgahinga Gorilla National Parks.
  • B. Rukungiri
    Rukungiri is a town in southwestern Uganda that serves as a regional center and gateway to nearby attractions such as Queen Elizabeth National Park.
  • C. Rutooro
    Rutooro is a Bantu language spoken primarily by the Tooro people in western Uganda.
  • D. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • E. 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.
  • 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: Rukiga
Triple: [Bantu E languages, hasMember, Rukiga]
Generated description
Rukiga is a Bantu language spoken primarily by the Bakiga people in southwestern Uganda.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rukiga
Target entity description: Rukiga is a Bantu language spoken primarily by the Bakiga people in southwestern Uganda.
  • A. Kisoro
    Kisoro is a small town in southwestern Uganda known as a gateway to gorilla trekking and the nearby Bwindi Impenetrable and Mgahinga Gorilla National Parks.
  • B. Rukungiri
    Rukungiri is a town in southwestern Uganda that serves as a regional center and gateway to nearby attractions such as Queen Elizabeth National Park.
  • C. Rutooro
    Rutooro is a Bantu language spoken primarily by the Tooro people in western Uganda.
  • D. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • E. 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.
  • 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_69ca82869ee08190b8f9040dbc2c0467 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb1a72cfdc8190a3186c4c2894f571 completed March 31, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbdf21add88190bc07d3164e940116 completed March 31, 2026, 2:50 p.m.
NEDg Description generation batch_69cc46bca04481908852425c214a4e34 completed March 31, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69cc49129e188190aaebd6a1188788d9 completed March 31, 2026, 10:22 p.m.
Created at: March 30, 2026, 4:51 p.m.