Triple

T14853051
Position Surface form Disambiguated ID Type / Status
Subject Faial Channel E349278 entity
Predicate connects P390 FINISHED
Object Madalena E332525 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: Madalena | Statement: [Faial Channel, connects, Madalena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madalena
Context triple: [Faial Channel, connects, Madalena]
  • A. Madalena chosen
    Madalena is a coastal town on the Azorean island of Pico in Portugal, known as a gateway to Mount Pico and for its wine culture and maritime heritage.
  • B. Madalena
    Madalena is a neighborhood in the Brazilian city of Recife, known for its urban character and local commerce.
  • C. Rosana
    Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
  • D. Rosana
    Rosana is a Brazilian professional footballer known for her successful international career and contributions to top women’s clubs, including Avaldsnes IL.
  • E. Maddalena
    Maddalena is the Italian form of the given name Magdalena, traditionally associated with Mary Magdalene in Christian tradition.
  • 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded441e70881909bbf62b66d932aff completed April 14, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b4ce76881909bf4a967da9357ae completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 1:54 a.m.