Triple

T16361093
Position Surface form Disambiguated ID Type / Status
Subject Alijó E397310 entity
Predicate borders P224 FINISHED
Object Vila Flor E397316 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: Vila Flor | Statement: [Alijó, borders, Vila Flor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vila Flor
Context triple: [Alijó, borders, Vila Flor]
  • A. Vila Flor chosen
    Vila Flor is a municipality in northern Portugal, situated in the Douro region known for its wine production and scenic landscapes.
  • B. Vila do Maio
    Vila do Maio is the main town and administrative center of Maio Island in Cape Verde, known for its coastal setting and role as the island’s primary hub.
  • C. Vila Facaia
    Vila Facaia is a civil parish located in the municipality of Pedrógão Grande in central Portugal.
  • D. Vila Viçosa
    Vila Viçosa is a historic town in Portugal renowned for its marble quarries and as a former residence of the Portuguese royal family.
  • E. Vila Baleira
    Vila Baleira is the main urban center and administrative hub of Porto Santo Island in Portugal’s Madeira archipelago, known for its proximity to long sandy beaches and historical ties to Christopher Columbus.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2fad304448190b3f6f0350a1e151d completed April 18, 2026, 3:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002dbeabe081909e3d02676293e8b2 completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:08 a.m.