Triple

T5915693
Position Surface form Disambiguated ID Type / Status
Subject Mirandés E131573 entity
Predicate hasDialect P4251 FINISHED
Object Mirandês central E23629 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: Mirandês central | Statement: [Mirandés, hasDialect, Mirandês central]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mirandês central
Context triple: [Mirandés, hasDialect, Mirandês central]
  • A. Mirandese language chosen
    Mirandese language is a minority Romance language spoken in northeastern Portugal, closely related to Astur-Leonese and recognized for its distinct cultural and linguistic heritage.
  • B. Beja language
    The Beja language is a Cushitic language spoken primarily by the Beja people across parts of Sudan, Egypt, and Eritrea.
  • C. Sendinês
    Sendinês is a regional dialect of the Mirandese language spoken in and around the village of Sendim in northeastern Portugal.
  • D. Haketia
    Haketia is a Judeo-Spanish dialect historically spoken by Sephardic Jews in northern Morocco and parts of Gibraltar, characterized by strong influences from Moroccan Arabic and Hebrew.
  • E. Azambuja
    Azambuja is a municipality in Portugal known for its agricultural landscape and proximity to the Lisbon metropolitan area.
  • 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_69c008593a44819081a07ae0efe6c574 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c037bb538c8190acc514c2d49359f4 completed March 22, 2026, 6:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c02430bc8190a63b91b6dbdbc9f2 completed March 23, 2026, 4:23 a.m.
Created at: March 22, 2026, 3:59 p.m.