Triple

T15914103
Position Surface form Disambiguated ID Type / Status
Subject Peter I of Portugal E385924 entity
Predicate associatedWith P37 FINISHED
Object Alcobaça 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: Alcobaça | Statement: [Peter I of Portugal, associatedWith, Alcobaça]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alcobaça
Context triple: [Peter I of Portugal, associatedWith, Alcobaça]
  • A. Alcobaça chosen
    Alcobaça is a historic Portuguese city best known for its UNESCO-listed Cistercian monastery, one of the country’s most important medieval monuments.
  • B. Lousã
    Lousã is a town and municipality in central Portugal known for its surrounding mountains, schist villages, and outdoor activities such as hiking and mountain biking.
  • C. Leiria
    Leiria is a historic city in central Portugal known for its medieval hilltop castle and role as a regional administrative and cultural center.
  • D. Caldas da Rainha
    Caldas da Rainha is a historic spa and market city in western Portugal, renowned for its thermal baths, ceramics tradition, and proximity to the Atlantic coast.
  • E. Lourinhã
    Lourinhã is a coastal municipality in western Portugal known for its rich dinosaur fossil discoveries and scenic Atlantic beaches.
  • 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_69d86da686e4819097cbf3b1fc2d881d completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15661046c819097a53de2a3e0443b completed April 16, 2026, 9:36 p.m.
Created at: April 10, 2026, 4:52 a.m.