Triple

T8931937
Position Surface form Disambiguated ID Type / Status
Subject Montserrado County E212676 entity
Predicate borders P224 FINISHED
Object Bomi County E194998 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: Bomi County | Statement: [Montserrado County, borders, Bomi County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bomi County
Context triple: [Montserrado County, borders, Bomi County]
  • A. Bomi County chosen
    Bomi County is an administrative region in western Liberia known for its role in the country’s civil conflicts and its predominantly rural, resource-rich landscape.
  • B. Nimba County
    Nimba County is a large, resource-rich county in northeastern Liberia that has been a significant site of political, ethnic, and military activity in the country’s modern history.
  • C. Buhera District
    Buhera District is an administrative district in eastern Zimbabwe known for its rural communities and agricultural activities.
  • D. Manyoni District
    Manyoni District is an administrative district in central Tanzania, known for its location along major transport routes and its largely rural, semi-arid landscape.
  • E. Turkana County
    Turkana County is a vast, arid county in northwestern Kenya known for its pastoralist communities, rich fossil and archaeological sites, and proximity to Lake Turkana.
  • 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_69ca8395c438819087d7cb844ab5990c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc668e5c108190b08f9cd6b4fd4a8b completed April 1, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba64dadc8190aea6f7528acab37a completed April 3, 2026, 1:02 p.m.
Created at: March 30, 2026, 6:57 p.m.