Triple

T15148606
Position Surface form Disambiguated ID Type / Status
Subject Monte Cassino E361878 entity
Predicate locatedNear P294 FINISHED
Object Cassino E161926 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: Cassino | Statement: [Monte Cassino, locatedNear, Cassino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cassino
Context triple: [Monte Cassino, locatedNear, Cassino]
  • A. Cassino chosen
    Cassino is a town in central Italy known for its strategic location and the nearby Monte Cassino, site of a historic Benedictine abbey and major World War II battles.
  • B. Seregno
    Seregno is a town in the Lombardy region of northern Italy, known for its industrial activity and proximity to Milan.
  • C. Castel di Sangro
    Castel di Sangro is a historic town in Italy’s Abruzzo region, known for its scenic Apennine mountain setting and as the subject of the football book "The Miracle of Castel di Sangro."
  • D. Campogalliano
    Campogalliano is a small Italian town and municipality in the Emilia-Romagna region, known for its industrial activity and proximity to the city of Modena.
  • E. Coriano
    Coriano is a municipality in Italy’s Emilia-Romagna region, known for its rural landscapes, historic center, and proximity to the Adriatic coast.
  • 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_69d85a0759908190b8a051d2e2a1cbe6 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e005c825a481909d00098b0e743365 completed April 15, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69febff281848190a094bd697b19aaf3 completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 3:07 a.m.