Triple

T19028279
Position Surface form Disambiguated ID Type / Status
Subject Halki E465667 entity
Predicate hasCapital P204 FINISHED
Object Emborio 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: Emborio | Statement: [Halki, hasCapital, Emborio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emborio
Context triple: [Halki, hasCapital, Emborio]
  • A. Emborio
    Emborio is a small coastal village that serves as the main port and one of the primary settlements on the Greek island of Kasos in the Aegean Sea.
  • B. Emborio chosen
    Emborio is the main harbor village and administrative center of the Greek island of Symi, known for its traditional neoclassical houses and picturesque waterfront.
  • C. Emborios
    Emborios is a small coastal village on the Greek island of Kalymnos, known for its tranquil atmosphere, traditional charm, and scenic bay.
  • D. Emborios
    Emborios is a small traditional village on the Greek island of Nisyros, known for its hillside setting and views over the volcanic landscape.
  • E. Alidoro
    Alidoro is the wise philosopher and tutor to Prince Ramiro in Rossini’s opera "La Cenerentola," who secretly guides and protects Cinderella.
  • 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_69d8dd0359648190bc2a9202c5cf29d2 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d73ec9088190a98e214bd56e8622 completed April 20, 2026, 7:35 a.m.
Created at: April 10, 2026, 12:02 p.m.