Triple

T3105844
Position Surface form Disambiguated ID Type / Status
Subject Agen E64826 entity
Predicate hasTwinTown P919 FINISHED
Object Toledo (Spain) E203762 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: Toledo (Spain) | Statement: [Agen, hasTwinTown, Toledo (Spain)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toledo (Spain)
Context triple: [Agen, hasTwinTown, Toledo (Spain)]
  • A. Toledo, Spain chosen
    Toledo, Spain is a historic Spanish city renowned for its medieval architecture, rich cultural heritage, and role as a setting in literature and art.
  • B. Oviedo
    Oviedo is the historic capital city of Spain’s Asturias region, known for its well-preserved medieval old town, pre-Romanesque churches, and role as a cultural and administrative center in northern Spain.
  • C. Valladolid
    Valladolid is a historic city in northwestern Spain that served as a major political and cultural center, including as a former capital of the Spanish monarchy.
  • D. Burgos
    Burgos is a historic city in northern Spain known for its medieval architecture and its prominent role during the Spanish Civil War.
  • E. Salamanca
    Salamanca is an industrial city in central Mexico known for its major oil refinery and role in the country's petrochemical sector.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada29beff08190b6e1eb6b0608d0eb completed March 8, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20388b7788190b78b9dd2671214ad completed March 12, 2026, 12:06 a.m.
Created at: March 8, 2026, 3:03 p.m.