Triple

T21346096
Position Surface form Disambiguated ID Type / Status
Subject Estremadura E526341 entity
Predicate contains P35 FINISHED
Object Mafra 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: Mafra | Statement: [Estremadura, contains, Mafra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mafra
Context triple: [Estremadura, contains, Mafra]
  • A. Mafra chosen
    Mafra is a Portuguese town best known for its monumental baroque National Palace and basilica, extensively built using local lioz limestone.
  • B. Nova Sintra
    Nova Sintra is the main town and administrative center of the island of Brava in Cape Verde, known for its colonial architecture and mountainous setting.
  • C. Mafra National Palace
    Mafra National Palace is a vast Baroque royal complex in Mafra, Portugal, renowned for its grand basilica, monumental convent, and one of Europe’s most important historic libraries.
  • D. Sintra
    Sintra is a historic Portuguese town near Lisbon, renowned for its romantic 19th-century palaces, castles, and lush hillside landscapes.
  • E. Vila Real
    Vila Real is a historic city in northern Portugal known for its scenic Douro Valley surroundings and notable Baroque architecture.
  • 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_69e0b51cd5cc81909ac1187971e8a8ad completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee5ba7ce3c8190ba5ded980a9866f2 completed April 26, 2026, 6:38 p.m.
Created at: April 16, 2026, 4:55 p.m.