Triple

T9035131
Position Surface form Disambiguated ID Type / Status
Subject Johanna Colón E216470 entity
Predicate familyName P18 FINISHED
Object Colón E738667 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: Colón | Statement: [Johanna Colón, familyName, Colón]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colón
Context triple: [Johanna Colón, familyName, Colón]
  • A. Colón
    Colón is a major Panamanian port city on the Caribbean coast, known as a key gateway to the Panama Canal and an important center for trade and shipping.
  • B. Colón
    Colón is a municipality and city in western Cuba known for its agricultural surroundings and colonial-era architecture.
  • C. Colón
    Colón is a riverside city in Argentina known for its tourism, hot springs, and access to the Uruguay River.
  • D. Colón
    Colón is a small municipality located in Colombia's southern Amazonian region within the Putumayo Department.
  • E. Colón chosen
    Colón is a Spanish-origin surname commonly found in Hispanic communities and notably borne by figures such as comic book artist Ernie Colón.
  • 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_69ca83d10b608190b2b2f8e0a7faaf14 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc6abf4af481908d21245332329d99 completed April 1, 2026, 12:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfeb8ec0588190a24b4a2aa443399f completed April 3, 2026, 4:32 p.m.
Created at: March 30, 2026, 7:08 p.m.