Triple

T8227229
Position Surface form Disambiguated ID Type / Status
Subject Corfinium E192202 entity
Predicate locatedInRegion P40 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: [Corfinium, locatedInRegion, Abruzzo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abruzzo
Context triple: [Corfinium, locatedInRegion, Abruzzo]
  • A. Abruzzo chosen
    Abruzzo is a central Italian region known for its rugged Apennine mountains, national parks, and Adriatic Sea coastline.
  • B. Molise
    Molise is a small, predominantly rural region in southern Italy known for its mountainous landscapes, traditional agriculture, and relatively low population density.
  • C. 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.
  • D. Umbria
    Umbria is a central Italian region known for its historic hill towns, medieval architecture, and rich cultural heritage.
  • E. Emilia-Romagna
    Emilia-Romagna is a region in northern Italy known for its rich culinary traditions, historic cities, and strong industrial and agricultural economy.
  • 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_69ca82db5b90819085d1ad7c2e27bfcc completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb77fdcb048190868ea4995b020a37 completed March 31, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd94e168688190aa0a7149a4f8c4b0 completed April 1, 2026, 9:57 p.m.
Created at: March 30, 2026, 5:46 p.m.