Triple

T13754030
Position Surface form Disambiguated ID Type / Status
Subject Bocas del Toro Province E330426 entity
Predicate hasCity P316 FINISHED
Object Almirante
Almirante is a coastal town in Panama known as a key port and transport hub in the Bocas del Toro region.
E1059625 NE FINISHED

How this triple was built (4 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: Almirante | Statement: [Bocas del Toro Province, hasCity, Almirante]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Almirante
Context triple: [Bocas del Toro Province, hasCity, Almirante]
  • A. Admiral Grant
    Admiral Grant is a fictional high-ranking naval officer portrayed by actor John Amos.
  • B. Coronel
    Coronel is a coastal city in south-central Chile known for its historic coal-mining industry and fishing activities along the Pacific Ocean.
  • C. Morison
    Morison is a surname most notably associated with Samuel Eliot Morison, the Pulitzer Prize–winning American historian and naval officer.
  • D. Tuğamiral
    Tuğamiral is a Turkish Navy flag officer rank equivalent to rear admiral (lower half) in many NATO navies.
  • E. Admiral Shane
    Admiral Shane is a high-ranking U.S. Navy officer and key military leader in the science fiction action film "Battleship."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Almirante
Triple: [Bocas del Toro Province, hasCity, Almirante]
Generated description
Almirante is a coastal town in Panama known as a key port and transport hub in the Bocas del Toro region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Almirante
Target entity description: Almirante is a coastal town in Panama known as a key port and transport hub in the Bocas del Toro region.
  • A. Admiral Grant
    Admiral Grant is a fictional high-ranking naval officer portrayed by actor John Amos.
  • B. Coronel
    Coronel is a coastal city in south-central Chile known for its historic coal-mining industry and fishing activities along the Pacific Ocean.
  • C. Morison
    Morison is a surname most notably associated with Samuel Eliot Morison, the Pulitzer Prize–winning American historian and naval officer.
  • D. Tuğamiral
    Tuğamiral is a Turkish Navy flag officer rank equivalent to rear admiral (lower half) in many NATO navies.
  • E. Admiral Shane
    Admiral Shane is a high-ranking U.S. Navy officer and key military leader in the science fiction action film "Battleship."
  • F. None of above. chosen

Provenance (5 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_69d81c573f288190aa2403d484fa3d49 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02179c948190a652cc8c586e418f completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7a85813e88190a63fecf8b0675df6 completed May 3, 2026, 7:56 p.m.
NEDg Description generation batch_69f7a968c3508190b1a86accb71b34cf completed May 3, 2026, 8 p.m.
NED2 Entity disambiguation (via description) batch_69f7aa2f696081908f48d44bf7271abc completed May 3, 2026, 8:03 p.m.
Created at: April 9, 2026, 10:09 p.m.