Triple

T36662837
Position Surface form Disambiguated ID Type / Status
Subject Agew people E905177 entity
Predicate historicalLanguageShiftInfluence P55689 FINISHED
Object development of Amharic LITERAL 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: development of Amharic | Statement: [Agew people, historicalLanguageShiftInfluence, development of Amharic]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: historicalLanguageShiftInfluence
Context triple: [Agew people, historicalLanguageShiftInfluence, development of Amharic]
  • A. historicalLanguageInfluenceOn chosen
    Indicates that one language has had a shaping or contributory effect on the development, vocabulary, structure, or usage of another language over time.
  • B. heritageLanguageShift
    Indicates a change over time in which a community or individual moves away from using their ancestral or heritage language toward another dominant language.
  • C. languageInfluence
    Indicates that one language has an effect on the development, usage, or characteristics of another language.
  • D. historicalLanguage
    Indicates that one language is a historical or earlier form/ancestor of another language.
  • E. causeOfLanguageShift
    Indicates a factor or event that leads to a change from one dominant language or linguistic pattern to another within a community or population.
  • F. None of above.

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_69f76e6e3b908190970251b30f76ad71 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_6a0143a4ab3c8190a240b0facfe130a9 completed May 11, 2026, 2:49 a.m.
PD Predicate disambiguation batch_6a01426b2d4481908654bfa4a02c457d completed May 11, 2026, 2:43 a.m.
Created at: May 3, 2026, 4:12 p.m.