Triple

T4084189
Position Surface form Disambiguated ID Type / Status
Subject Matilda of Tuscany E87548 entity
Predicate controlledTerritory P16398 FINISHED
Object Tuscany E34826 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: Tuscany | Statement: [Matilda of Tuscany, controlledTerritory, Tuscany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tuscany
Context triple: [Matilda of Tuscany, controlledTerritory, Tuscany]
  • A. Tuscany chosen
    Tuscany is a central Italian region renowned for its rolling landscapes, historic cities like Florence and Siena, and its pivotal role in art, culture, and the birth of the Renaissance.
  • B. Umbria
    Umbria is a central Italian region known for its historic hill towns, medieval architecture, and rich cultural heritage.
  • C. Liguria
    Liguria is a coastal region in northwestern Italy known for its picturesque Riviera, including the Cinque Terre and the city of Genoa.
  • D. Maremma region
    The Maremma region is a coastal area of southwestern Tuscany and northern Lazio in Italy, known for its wild landscapes, medieval hill towns, and traditional agriculture.
  • E. Senigallia
    Senigallia is a historic coastal town in Italy’s Marche region, known for its Adriatic seaside resort, Renaissance heritage, and well-preserved old town.
  • 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_69aed9435cf48190ad1da737c962d19d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc7a4b488190ab466e2c50329ab3 completed March 9, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562c9760c8190a9292eb1cea55ab2 completed March 14, 2026, 1:29 p.m.
Created at: March 9, 2026, 3:39 p.m.