Triple

T17154271
Position Surface form Disambiguated ID Type / Status
Subject Afabet E416301 entity
Predicate languageSpoken P151 FINISHED
Object Tigrinya E41857 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: Tigrinya | Statement: [Afabet, languageSpoken, Tigrinya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tigrinya
Context triple: [Afabet, languageSpoken, Tigrinya]
  • A. Tigrinya chosen
    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.
  • B. Amharic
    Amharic is a Semitic language widely spoken in Ethiopia and used as a major language of government, education, and media in the country.
  • C. 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.
  • D. Ge'ez
    Ge'ez is an ancient Semitic language of Ethiopia and Eritrea, best known today as the classical and liturgical language of the Ethiopian and Eritrean Orthodox Tewahedo Churches.
  • E. 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.
  • 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f4092c40819096359ff90af16c3e completed April 18, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01415f3cd481908e96ca294cf3b247 completed May 11, 2026, 2:39 a.m.
Created at: April 10, 2026, 5:37 a.m.