Triple

T14998612
Position Surface form Disambiguated ID Type / Status
Subject Tanga Region E374023 entity
Predicate borders P224 FINISHED
Object Pwani Region E832695 NE FINISHED

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: Pwani Region | Statement: [Tanga Region, borders, Pwani Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pwani Region
Context triple: [Tanga Region, borders, Pwani Region]
  • A. Pwani Region chosen
    Pwani Region is a coastal administrative region in eastern Tanzania known for its Swahili culture, Indian Ocean shoreline, and proximity to Dar es Salaam.
  • B. Dar es Salaam Region
    Dar es Salaam Region is a coastal administrative region in eastern Tanzania that encompasses the country’s largest city and main economic hub.
  • C. Nyanza region
    Nyanza region is an area in western Kenya along Lake Victoria, known for its predominantly Luo population and the city of Kisumu as its main urban center.
  • D. Mwanza Region
    Mwanza Region is an administrative region in northwestern Tanzania, located along the southern shores of Lake Victoria and known as a major economic and cultural center, including for the Sukuma people.
  • E. Singida Region
    Singida Region is an administrative region in central Tanzania known for its semi-arid climate, agriculture, and role as a transport crossroads.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded71a5618819083ae96a79735ef98 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff01d6ddbc81908b010a54ee728dfe completed May 9, 2026, 9:43 a.m.
Created at: April 10, 2026, 2:54 a.m.