Triple

T331212
Position Surface form Disambiguated ID Type / Status
Subject Christopher Columbus E6628 entity
Predicate shipCommanded P884 FINISHED
Object Niña
Niña was one of the three ships in Christopher Columbus’s 1492 voyage across the Atlantic, notable for its role in the first European expedition to the Americas.
 E43364 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: Niña | Statement: [Christopher Columbus, shipCommanded, Niña]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Niña
Context triple: [Christopher Columbus, shipCommanded, Niña]
  • A. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • B. Alicia
    Alicia is the given name of the American singer, songwriter, and pianist Alicia Keys, known for her soulful R&B music and powerful vocals.
  • C. Hilda
    Hilda is the middle name of Margaret Thatcher, the former Prime Minister of the United Kingdom.
  • D. Miguel
    Miguel is an American R&B singer, songwriter, and producer known for his smooth vocals and genre-blending, atmospheric sound.
  • E. Rebeca
    Rebeca is a feminine given name, commonly used in Spanish- and Portuguese-speaking countries, that is a variant of the name Rebecca.
  • 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: Niña
Triple: [Christopher Columbus, shipCommanded, Niña]
Generated description
Niña was one of the three ships in Christopher Columbus’s 1492 voyage across the Atlantic, notable for its role in the first European expedition to the Americas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Niña
Target entity description: Niña was one of the three ships in Christopher Columbus’s 1492 voyage across the Atlantic, notable for its role in the first European expedition to the Americas.
  • A. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • B. Alicia
    Alicia is the given name of the American singer, songwriter, and pianist Alicia Keys, known for her soulful R&B music and powerful vocals.
  • C. Hilda
    Hilda is the middle name of Margaret Thatcher, the former Prime Minister of the United Kingdom.
  • D. Miguel
    Miguel is an American R&B singer, songwriter, and producer known for his smooth vocals and genre-blending, atmospheric sound.
  • E. Rebeca
    Rebeca is a feminine given name, commonly used in Spanish- and Portuguese-speaking countries, that is a variant of the name Rebecca.
  • 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_69a2e79434908190a9d5afe415153ad9 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2eaafd1a48190a6d001af3c2a5318 completed Feb. 28, 2026, 1:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3d4e23894819088b2d276cfb9d26d completed March 1, 2026, 5:55 a.m.
NEDg Description generation batch_69a3d5ac92648190a06cb00de270dc51 completed March 1, 2026, 5:59 a.m.
NED2 Entity disambiguation (via description) batch_69a3d64a8a4c8190b5547398d167393e completed March 1, 2026, 6:01 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.