Triple

T18045974
Position Surface form Disambiguated ID Type / Status
Subject Val di Chiana E431773 entity
Predicate majorTown P316 FINISHED
Object Chianciano Terme NE NERFINISHED

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: Chianciano Terme | Statement: [Val di Chiana, majorTown, Chianciano Terme]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chianciano Terme
Context triple: [Val di Chiana, majorTown, Chianciano Terme]
  • A. Chianciano Terme chosen
    Chianciano Terme is a renowned spa town in Tuscany, central Italy, famous for its therapeutic thermal waters and wellness tourism.
  • B. San Giuliano Terme
    San Giuliano Terme is an Italian town in Tuscany known for its historic thermal baths and proximity to the city of Pisa.
  • C. San Giovanni Teatino
    San Giovanni Teatino is a municipality in the Abruzzo region of central Italy, situated between Pescara and Chieti and known for its residential areas and commercial–industrial zones.
  • D. Musignano
    Musignano is an Italian locality historically linked to the Bonaparte family’s expanded heraldic and territorial holdings.
  • E. Monterotondo Marittimo
    Monterotondo Marittimo is a small Tuscan municipality in central Italy, known for its geothermal landscapes and medieval hilltop setting.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b906482481908183315b9ecf9994 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4bff202088190ae971879348e2294 completed April 19, 2026, 11:43 a.m.
Created at: April 10, 2026, 10:25 a.m.