Triple

T4289467
Position Surface form Disambiguated ID Type / Status
Subject Gash-Barka E97352 entity
Predicate bordersRegion P224 FINISHED
Object Anseba E105070 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: Anseba | Statement: [Gash-Barka, bordersRegion, Anseba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anseba
Context triple: [Gash-Barka, bordersRegion, Anseba]
  • A. Anseba chosen
    Anseba is a central region of Eritrea known for its diverse ethnic communities, agriculture, and the regional capital Keren.
  • B. Buhera
    Buhera is a rural town and district center in eastern Zimbabwe known for its agricultural activities and location within Manicaland Province.
  • C. Takrur
    Takrur was an early West African kingdom located in the Senegal River valley, known for its role in trans-Saharan trade and its early adoption of Islam.
  • D. Birsay
    Birsay is a coastal parish and village area on the northwest of Orkney Mainland in Scotland, known for its rich Norse history and archaeological sites.
  • E. Kenuzi-Dongola
    Kenuzi-Dongola is a Nubian language of the Eastern Sudanic branch spoken primarily along the Nile in southern Egypt and northern Sudan.
  • 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_69b3454595848190a0e6bbb6a2bea040 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35061f5448190b3356b29a9129160 completed March 12, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c7307e3481909dfb55018f359589 completed March 14, 2026, 8:38 p.m.
Created at: March 12, 2026, 11:08 p.m.