Triple

T3193613
Position Surface form Disambiguated ID Type / Status
Subject Pico Island E66882 entity
Predicate hasMainSettlement P2106 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: [Pico Island, hasMainSettlement, Madalena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madalena
Context triple: [Pico Island, hasMainSettlement, 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. Maddalena
    Maddalena is the Italian form of the given name Magdalena, traditionally associated with Mary Magdalene in Christian tradition.
  • D. Isabela
    Isabela is a large agricultural province in the Cagayan Valley region of the Philippines, known especially for its extensive rice and corn production.
  • E. María
    María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
  • 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_69ad8588ba18819086a10951c32ecb80 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada713bf0c81908f3143f45f63a5ad completed March 8, 2026, 4:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b276fbb7c481909097f5af619e45f4 completed March 12, 2026, 8:19 a.m.
Created at: March 8, 2026, 3:07 p.m.