Triple

T4691017
Position Surface form Disambiguated ID Type / Status
Subject Lioz limestone E104032 entity
Predicate notableUseInCity P4810 FINISHED
Object Mafra E462967 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: Mafra | Statement: [Lioz limestone, notableUseInCity, Mafra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mafra
Context triple: [Lioz limestone, notableUseInCity, 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. Sintra
    Sintra is a historic Portuguese town near Lisbon, renowned for its romantic 19th-century palaces, castles, and lush hillside landscapes.
  • D. Vila Real
    Vila Real is a historic city in northern Portugal known for its scenic Douro Valley surroundings and notable Baroque architecture.
  • E. Vila de Rei
    Vila de Rei is a small inland municipality in central Portugal known for its rural landscapes and its location near the country’s geodesic center.
  • 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_69bd43df91f481908e9add1b617b60ef completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6c3d1cb88190a42919dcbfe2568c completed March 20, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69be105a709c819083504fe1dc1612d8 completed March 21, 2026, 3:28 a.m.
Created at: March 20, 2026, 1:16 p.m.