Triple

T5375845
Position Surface form Disambiguated ID Type / Status
Subject Ituri Province E108956 entity
Predicate hasCity P316 FINISHED
Object Mambasa
Mambasa is a town and administrative center located in the forested Ituri region of northeastern Democratic Republic of the Congo.
 E516363 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: Mambasa | Statement: [Ituri Province, hasCity, Mambasa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mambasa
Context triple: [Ituri Province, hasCity, Mambasa]
  • A. Mzuzu
    Mzuzu is a major city in northern Malawi known as an important commercial and administrative center for the region.
  • B. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • C. Mvita
    Mvita is an alternative name for Kimvita, a historic Swahili settlement and cultural center on the coast of present-day Kenya.
  • D. Barawa
    Barawa is a West Chadic language spoken in parts of Nigeria, belonging to the Afroasiatic language family.
  • E. Makoni
    Makoni is a town in Zimbabwe’s Manicaland Province, known primarily as a local administrative and commercial center for the surrounding rural 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: Mambasa
Triple: [Ituri Province, hasCity, Mambasa]
Generated description
Mambasa is a town and administrative center located in the forested Ituri region of northeastern Democratic Republic of the Congo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mambasa
Target entity description: Mambasa is a town and administrative center located in the forested Ituri region of northeastern Democratic Republic of the Congo.
  • A. Mzuzu
    Mzuzu is a major city in northern Malawi known as an important commercial and administrative center for the region.
  • B. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • C. Mvita
    Mvita is an alternative name for Kimvita, a historic Swahili settlement and cultural center on the coast of present-day Kenya.
  • D. Barawa
    Barawa is a West Chadic language spoken in parts of Nigeria, belonging to the Afroasiatic language family.
  • E. Makoni
    Makoni is a town in Zimbabwe’s Manicaland Province, known primarily as a local administrative and commercial center for the surrounding rural 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_69bd440c77948190aad2a5f39b7b80f5 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd86aed2a8819089d9e699f53563db completed March 20, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf293f6458819091c32080782b56ed completed March 21, 2026, 11:26 p.m.
NEDg Description generation batch_69bf2a23ba1881909ddc549728bbc2d3 completed March 21, 2026, 11:30 p.m.
NED2 Entity disambiguation (via description) batch_69bf2e6d5f9081908327dff0058241f0 completed March 21, 2026, 11:49 p.m.
Created at: March 20, 2026, 2:03 p.m.