Triple

T4916989
Position Surface form Disambiguated ID Type / Status
Subject Yonas E110373 entity
Predicate hasLanguageUsage P207 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: [Yonas, hasLanguageUsage, Amharic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amharic
Context triple: [Yonas, hasLanguageUsage, 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_69bd44132b94819088522d92beaadc78 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6fa559608190aa8d02b1547b8f97 completed March 20, 2026, 4:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81bfb44481909f67d726dacec37d completed March 21, 2026, 11:32 a.m.
Created at: March 20, 2026, 1:29 p.m.