Triple

T15570370
Position Surface form Disambiguated ID Type / Status
Subject Beiras E374222 entity
Predicate hasCity P316 FINISHED
Object Guarda E199962 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: Guarda | Statement: [Beiras, hasCity, Guarda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guarda
Context triple: [Beiras, hasCity, Guarda]
  • A. Guarda
    Guarda is a picturesque historic village in Switzerland’s Engadine valley, renowned for its well-preserved traditional houses and alpine scenery.
  • B. Guarda chosen
    Guarda is a historic city in central Portugal known for being the country's highest-altitude city and for its well-preserved medieval architecture.
  • C. Guardo
    Guardo is a small town in northern Spain known for its location in the mountainous province of Palencia within the autonomous community of Castile and León.
  • D. Guardea
    Guardea is a small Italian town and comune in the Umbria region, known for its medieval historic center and scenic position overlooking the Tiber Valley.
  • E. Guardino
    Guardino is an Italian-origin surname borne by various notable individuals, including American actor Harry Guardino.
  • 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e1de0488190b3639fc25f79d343 completed April 16, 2026, 2:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f30e48881908b30a71796fe0d72 completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:10 a.m.