Triple

T20354428
Position Surface form Disambiguated ID Type / Status
Subject Morogoro Region E496104 entity
Predicate bordersRegion P224 FINISHED
Object Dar es Salaam Region NE NERFINISHED

How this triple was built (2 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: Dar es Salaam Region | Statement: [Morogoro Region, bordersRegion, Dar es Salaam Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dar es Salaam Region
Context triple: [Morogoro Region, bordersRegion, Dar es Salaam Region]
  • A. Dar es Salaam Region chosen
    Dar es Salaam Region is a coastal administrative region in eastern Tanzania that encompasses the country’s largest city and main economic hub.
  • B. Pwani Region
    Pwani Region is a coastal administrative region in eastern Tanzania known for its Swahili culture, Indian Ocean shoreline, and proximity to Dar es Salaam.
  • C. Iringa Region
    Iringa Region is an administrative area in south-central Tanzania known for its highland landscapes and as the gateway to Ruaha National Park, one of the country’s largest wildlife reserves.
  • D. Dodoma Region
    Dodoma Region is an administrative region in central Tanzania that includes the national capital city, Dodoma.
  • E. Njombe Region
    Njombe Region is an administrative region in southern Tanzania known for its highland climate, agriculture (especially tea and timber), and proximity to the Southern Highlands.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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.
Created at: April 16, 2026, 11:25 a.m.