Triple

T9526910
Position Surface form Disambiguated ID Type / Status
Subject Arbëreshë people E229781 entity
Predicate primaryRegionsInItaly P88159 FINISHED
Object Abruzzo E69244 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: Abruzzo | Statement: [Arbëreshë people, primaryRegionsInItaly, Abruzzo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abruzzo
Context triple: [Arbëreshë people, primaryRegionsInItaly, Abruzzo]
  • A. Abruzzo chosen
    Abruzzo is a central Italian region known for its rugged Apennine mountains, national parks, and Adriatic Sea coastline.
  • B. D’Abruzzo
    D’Abruzzo is an Italian surname associated with actor Robert Alda, reflecting his family’s Abruzzese heritage.
  • C. Molise
    Molise is a small, predominantly rural region in southern Italy known for its mountainous landscapes, traditional agriculture, and relatively low population density.
  • D. La Marche
    La Marche is a historic province in central France known for its rural landscapes and role as a frontier region between major medieval territories.
  • E. Umbria
    Umbria is a central Italian region known for its historic hill towns, medieval architecture, and rich cultural heritage.
  • 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_69ca8479934c81908006d0e6e970ae05 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd989c831081908877e42f7ead84ba completed April 1, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19f5cd12881909fb1524a972448ee completed April 4, 2026, 11:31 p.m.
Created at: March 30, 2026, 8 p.m.