Triple

T20072125
Position Surface form Disambiguated ID Type / Status
Subject Tanganyika Province E499762 entity
Predicate hasCity P316 FINISHED
Object Nyunzu
Nyunzu is a town and administrative center in southeastern Democratic Republic of the Congo, known for its role as a local hub in Tanganyika Province.
E1410105 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: Nyunzu | Statement: [Tanganyika Province, hasCity, Nyunzu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nyunzu
Context triple: [Tanganyika Province, hasCity, Nyunzu]
  • A. Nganzai
    Nganzai is a local government area in Borno State, northeastern Nigeria, known for its rural communities and impact from the Boko Haram insurgency.
  • B. Yokadouma
    Yokadouma is a town in eastern Cameroon that serves as an important local administrative and commercial center near the country's forested border regions.
  • C. Goura
    Goura is a small village in the Peloponnese region of Greece, known for its traditional stone architecture and mountainous surroundings.
  • D. Isanzu
    Isanzu is a Bantu language spoken by the Isanzu people of north-central Tanzania.
  • E. Nuriro
    Nuriro is a class of South Korean intercity passenger trains operated by Korail, providing medium-speed rail services on various routes.
  • 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: Nyunzu
Triple: [Tanganyika Province, hasCity, Nyunzu]
Generated description
Nyunzu is a town and administrative center in southeastern Democratic Republic of the Congo, known for its role as a local hub in Tanganyika Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nyunzu
Target entity description: Nyunzu is a town and administrative center in southeastern Democratic Republic of the Congo, known for its role as a local hub in Tanganyika Province.
  • A. Nganzai
    Nganzai is a local government area in Borno State, northeastern Nigeria, known for its rural communities and impact from the Boko Haram insurgency.
  • B. Yokadouma
    Yokadouma is a town in eastern Cameroon that serves as an important local administrative and commercial center near the country's forested border regions.
  • C. Goura
    Goura is a small village in the Peloponnese region of Greece, known for its traditional stone architecture and mountainous surroundings.
  • D. Isanzu
    Isanzu is a Bantu language spoken by the Isanzu people of north-central Tanzania.
  • E. Nuriro
    Nuriro is a class of South Korean intercity passenger trains operated by Korail, providing medium-speed rail services on various routes.
  • 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66438633481908710907c48806499 completed April 20, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a081f3d1ad48190b434568a0c0d60de completed May 16, 2026, 7:39 a.m.
NEDg Description generation batch_6a08203132d48190b3f1313dae3e6fc1 completed May 16, 2026, 7:43 a.m.
NED2 Entity disambiguation (via description) batch_6a0821390af08190a4aca33d33f0e71d completed May 16, 2026, 7:48 a.m.
Created at: April 11, 2026, 3:40 p.m.