Triple

T19987131
Position Surface form Disambiguated ID Type / Status
Subject Valdelsa E493962 entity
Predicate containsSettlement P847 FINISHED
Object Poggibonsi 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: Poggibonsi | Statement: [Valdelsa, containsSettlement, Poggibonsi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Poggibonsi
Context triple: [Valdelsa, containsSettlement, Poggibonsi]
  • A. Poggibonsi chosen
    Poggibonsi is a Tuscan town in central Italy known for its medieval history, archaeological sites, and position along historic pilgrimage and trade routes between Florence and Siena.
  • B. Montemurlo
    Montemurlo is a municipality in the Tuscany region of central Italy, known for its industrial activity and proximity to the city of Prato.
  • C. Pieve Santo Stefano
    Pieve Santo Stefano is a small Tuscan town in central Italy, known for its historic architecture and scenic setting in the province of Arezzo.
  • D. Bagnacavallo
    Bagnacavallo is a historic town in Italy’s Emilia-Romagna region, known for its well-preserved medieval center and traditional rural culture.
  • E. Bibbiena
    Bibbiena is a historic town and municipality in Tuscany, central Italy, known for its medieval architecture and scenic setting in the Casentino valley.
  • 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_69da626a67648190af9653832a3aeced completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e65fdd1a5c8190af756632aac38bf4 completed April 20, 2026, 5:18 p.m.
Created at: April 11, 2026, 3:29 p.m.