Triple

T7267313
Position Surface form Disambiguated ID Type / Status
Subject Holguín Province E161008 entity
Predicate hasCity P316 FINISHED
Object Gibara E368650 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: Gibara | Statement: [Holguín Province, hasCity, Gibara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gibara
Context triple: [Holguín Province, hasCity, Gibara]
  • A. Gibara chosen
    Gibara is a small coastal town in northeastern Cuba known for its colonial architecture, fishing traditions, and annual international film festival.
  • B. Guanaja
    Guanaja is one of Honduras's Bay Islands in the Caribbean Sea, known for its lush mountainous terrain, coral reefs, and small English-speaking communities.
  • C. Jarabacoa
    Jarabacoa is a mountainous town in the Dominican Republic known for its cool climate, rivers, and outdoor adventure tourism.
  • D. Isla Margarita
    Isla Margarita is a popular Caribbean island of Venezuela known for its beaches, tourism, and historical role in the country’s independence.
  • E. Baracoa
    Baracoa is a historic coastal city in eastern Cuba, known as the island’s oldest Spanish settlement and for its lush tropical landscape and cocoa production.
  • 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_69c6885181008190b419040e22939c7c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eae7b2108190a6910f6655669db5 completed March 27, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d3cd94d48190951759560e9891d7 completed March 28, 2026, 1:12 p.m.
Created at: March 27, 2026, 2:58 p.m.