Triple

T21713849
Position Surface form Disambiguated ID Type / Status
Subject Kinyankole language E535971 entity
Predicate alternativeName P39 FINISHED
Object Orunyankore
Orunyankore is a Bantu language spoken primarily by the Banyankore people in southwestern Uganda.
E1497641 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: Orunyankore | Statement: [Kinyankole language, alternativeName, Orunyankore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orunyankore
Context triple: [Kinyankole language, alternativeName, Orunyankore]
  • A. Githunguri
    Githunguri is a town in Kenya known for its agricultural activities, particularly dairy and coffee farming, within Kiambu County.
  • B. Nakasero
    Nakasero is a central and upscale neighborhood in Kampala, Uganda, known for its government offices, embassies, hotels, and commercial centers.
  • C. Akuku
    Akuku is a settlement located within the Akoko-Edo area of Edo State in southern Nigeria.
  • D. Wunda
    Wunda is a figure from Australian Aboriginal mythology, often regarded as a heroic or ancestral spirit.
  • E. Erg Chigaga
    Erg Chigaga is a vast, remote dune field in southern Morocco known for its towering sand dunes and desert wilderness landscapes.
  • 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: Orunyankore
Triple: [Kinyankole language, alternativeName, Orunyankore]
Generated description
Orunyankore is a Bantu language spoken primarily by the Banyankore people in southwestern Uganda.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Orunyankore
Target entity description: Orunyankore is a Bantu language spoken primarily by the Banyankore people in southwestern Uganda.
  • A. Githunguri
    Githunguri is a town in Kenya known for its agricultural activities, particularly dairy and coffee farming, within Kiambu County.
  • B. Nakasero
    Nakasero is a central and upscale neighborhood in Kampala, Uganda, known for its government offices, embassies, hotels, and commercial centers.
  • C. Akuku
    Akuku is a settlement located within the Akoko-Edo area of Edo State in southern Nigeria.
  • D. Wunda
    Wunda is a figure from Australian Aboriginal mythology, often regarded as a heroic or ancestral spirit.
  • E. Erg Chigaga
    Erg Chigaga is a vast, remote dune field in southern Morocco known for its towering sand dunes and desert wilderness landscapes.
  • 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_69e0c46c6dd88190a595375fa6ebd701 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69efb5369be88190bafc10863d4d1bd7 completed April 27, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a24b180bc8190bef4daaab7de794d completed May 17, 2026, 8:27 p.m.
NEDg Description generation batch_6a0a261cdb788190b06939c4786e41ce completed May 17, 2026, 8:33 p.m.
NED2 Entity disambiguation (via description) batch_6a0a267dec7881908b5cb9d9a83f97c4 completed May 17, 2026, 8:35 p.m.
Created at: April 16, 2026, 6:47 p.m.