Triple

T6183591
Position Surface form Disambiguated ID Type / Status
Subject Pescina E138001 entity
Predicate province P604 FINISHED
Object L'Aquila E347601 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: L'Aquila | Statement: [Pescina, province, L'Aquila]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: L'Aquila
Context triple: [Pescina, province, L'Aquila]
  • A. L'Aquila chosen
    L'Aquila is a historic city in central Italy known for its medieval architecture and as the administrative and cultural center of the surrounding mountainous region.
  • B. Frosinone
    Frosinone is a city in central Italy that serves as the capital of the province of the same name within the Lazio region.
  • C. Isernia
    Isernia is a historic town and provincial capital in the Molise region of southern-central Italy, known for its ancient Samnite and Roman roots.
  • D. Rieti
    Rieti is a historic town in central Italy often considered the geographical center of the country and known for its medieval architecture and proximity to the Apennine Mountains.
  • E. Teramo
    Teramo is a historic city in the Abruzzo region of central Italy, known for its Roman archaeological remains and medieval architecture.
  • 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_69c008a8fd408190b7ec6e42934974a6 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06100c2b0819097f287e86f63d590 completed March 22, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c141c6b5888190983bff620c7663cc completed March 23, 2026, 1:36 p.m.
Created at: March 22, 2026, 4:19 p.m.