Triple

T14998525
Position Surface form Disambiguated ID Type / Status
Subject Siha District E374021 entity
Predicate borders P224 FINISHED
Object Moshi Rural District E374019 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: Moshi Rural District | Statement: [Siha District, borders, Moshi Rural District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moshi Rural District
Context triple: [Siha District, borders, Moshi Rural District]
  • A. Moshi Rural District chosen
    Moshi Rural District is an administrative district in northern Tanzania known for its agricultural communities and proximity to Mount Kilimanjaro.
  • B. Shindand District
    Shindand District is an administrative district in western Afghanistan known for its strategic location and the nearby Shindand Air Base.
  • C. Mirzaka District
    Mirzaka District is an administrative district located within Paktia Province in eastern Afghanistan.
  • D. Pishin District
    Pishin District is an administrative district in the Balochistan province of Pakistan, known for its agricultural economy and predominantly Pashtun population.
  • E. Musa Qala District
    Musa Qala District is an administrative district in northern Helmand Province, Afghanistan, known for its strategic location and history of intense conflict during the Afghan war.
  • 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_69fe969c3ba88190899f06b185e94ccf completed May 9, 2026, 2:06 a.m.
Created at: April 10, 2026, 2:54 a.m.