Triple

T18839099
Position Surface form Disambiguated ID Type / Status
Subject Monte Verde E460743 entity
Predicate hasNameInLanguage P15 FINISHED
Object Monte Verde (Portuguese) 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: Monte Verde (Portuguese) | Statement: [Monte Verde, hasNameInLanguage, Monte Verde (Portuguese)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monte Verde (Portuguese)
Context triple: [Monte Verde, hasNameInLanguage, Monte Verde (Portuguese)]
  • A. Monte Verde chosen
    Monte Verde is a notable mountain located on the island of São Vicente in Cape Verde, known for its prominent peak and scenic views.
  • B. Monte Verde site
    The Monte Verde site is an archaeological location in southern Chile that provides some of the earliest widely accepted evidence of human presence in the Americas, challenging the traditional Clovis-first model.
  • C. Idanha-a-Velha
    Idanha-a-Velha is a historic village in central Portugal renowned for its well-preserved Roman and medieval archaeological remains.
  • D. Vila Verde
    Vila Verde is a municipality in the Braga District of northern Portugal, known for its rural landscapes and traditional Minho culture.
  • E. Vila Verde
    Vila Verde is a civil parish within the coastal municipality of Figueira da Foz in central Portugal.
  • 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_69d8dcfa11e4819090ab1ef5bdcd2b2e completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5a9a0a9a48190b19b131f06b6f72f completed April 20, 2026, 4:20 a.m.
Created at: April 10, 2026, 11:56 a.m.