Triple

T4122918
Position Surface form Disambiguated ID Type / Status
Subject Saho E92654 entity
Predicate hasLexicalBorrowingFrom P1754 FINISHED
Object Amharic E41109 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: Amharic | Statement: [Saho, hasLexicalBorrowingFrom, Amharic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amharic
Context triple: [Saho, hasLexicalBorrowingFrom, Amharic]
  • A. Amharic chosen
    Amharic is a Semitic language widely spoken in Ethiopia and used as a major language of government, education, and media in the country.
  • B. Tigrinya
    Tigrinya is a Semitic language spoken primarily in Eritrea and northern Ethiopia, serving as a major language of communication, education, and media in the region.
  • C. Ethiopian
    Ethiopian refers to a person from Ethiopia or of Ethiopian descent, associated with the country's distinct cultures, languages, and history in the Horn of Africa.
  • D. Eritrean
    Eritrean refers to someone or something originating from Eritrea, a country in the Horn of Africa known for its diverse ethnic groups and Red Sea coastline.
  • E. ETHIOPIAN
    ETHIOPIAN is the radio callsign used by Ethiopian Airlines for its flight operations and air traffic communications.
  • 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_69aed9685f70819086932777aec8d959 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69af020728a08190a50a16b40690cbce completed March 9, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f256abc819086cd464be1a9efbf completed March 14, 2026, 3:30 p.m.
Created at: March 9, 2026, 3:41 p.m.