Triple

T20354422
Position Surface form Disambiguated ID Type / Status
Subject Morogoro Region E496104 entity
Predicate containsCity P294 FINISHED
Object Kilosa
Kilosa is a town and district in eastern Tanzania known for its agricultural activities and location along the central railway in the Morogoro Region.
E1425602 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: Kilosa | Statement: [Morogoro Region, containsCity, Kilosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kilosa
Context triple: [Morogoro Region, containsCity, Kilosa]
  • A. Kilana
    Kilana is a Vorta official serving the Dominion who appears in Star Trek: Deep Space Nine as a cunning and diplomatic antagonist.
  • B. Kilo
    Kilo is a residential district in the city of Espoo, Finland, known for its apartment blocks, local services, and good commuter rail connections to Helsinki and surrounding areas.
  • C. Kilo
    Kilo is a hip-hop track by Clipse known for its vivid, metaphor-laden depictions of cocaine dealing.
  • D. Quintal
    Quintal is a small commune in the Haute-Savoie department of southeastern France, situated near Annecy in the French Alps.
  • E. Kilolo
    Kilolo is a town in southern Tanzania that serves as an administrative and local commercial center within the Iringa Region.
  • 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: Kilosa
Triple: [Morogoro Region, containsCity, Kilosa]
Generated description
Kilosa is a town and district in eastern Tanzania known for its agricultural activities and location along the central railway in the Morogoro Region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kilosa
Target entity description: Kilosa is a town and district in eastern Tanzania known for its agricultural activities and location along the central railway in the Morogoro Region.
  • A. Kilana
    Kilana is a Vorta official serving the Dominion who appears in Star Trek: Deep Space Nine as a cunning and diplomatic antagonist.
  • B. Kilo
    Kilo is a residential district in the city of Espoo, Finland, known for its apartment blocks, local services, and good commuter rail connections to Helsinki and surrounding areas.
  • C. Kilo
    Kilo is a hip-hop track by Clipse known for its vivid, metaphor-laden depictions of cocaine dealing.
  • D. Quintal
    Quintal is a small commune in the Haute-Savoie department of southeastern France, situated near Annecy in the French Alps.
  • E. Kilolo
    Kilolo is a town in southern Tanzania that serves as an administrative and local commercial center within the Iringa Region.
  • 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_69e0b4a3f7f48190b37f354574028ca6 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67852ca9881908a5af18005639859 completed April 20, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a086968a4d8819090d5fbb3229724f7 completed May 16, 2026, 12:56 p.m.
NEDg Description generation batch_6a0869b998108190a5c6652c2f5f2f5d completed May 16, 2026, 12:57 p.m.
NED2 Entity disambiguation (via description) batch_6a086a6812a08190b4594fa9b6054355 completed May 16, 2026, 1 p.m.
Created at: April 16, 2026, 11:25 a.m.