Triple

T9527011
Position Surface form Disambiguated ID Type / Status
Subject Lungro E229783 entity
Predicate province P604 FINISHED
Object Cosenza E328742 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: Cosenza | Statement: [Lungro, province, Cosenza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cosenza
Context triple: [Lungro, province, Cosenza]
  • A. Cosenza chosen
    Cosenza is a historic city in southern Italy known for its medieval old town, cultural heritage, and role as an important provincial and university center.
  • B. Catanzaro
    Catanzaro is a city in southern Italy known as an administrative and cultural center overlooking the Ionian Sea.
  • C. Reggio Calabria
    Reggio Calabria is a historic coastal city in the Calabria region, known as the largest urban center at the tip of Italy’s “boot” facing Sicily across the Strait of Messina.
  • D. Trani
    Trani is a historic coastal city in the Apulia region of southern Italy, known for its medieval architecture and picturesque harbor on the Adriatic Sea.
  • E. Aversa
    Aversa is a historic city in southern Italy’s Campania region, known for its medieval origins and proximity to Naples.
  • 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_69d2cb2aaef481908a7be61bbfc3b008 completed April 5, 2026, 8:50 p.m.
Created at: March 30, 2026, 8 p.m.