Triple

T5341370
Position Surface form Disambiguated ID Type / Status
Subject 2005 Atlantic hurricane season E123950 entity
Predicate retiredStormName P23042 FINISHED
Object Wilma
Wilma was a catastrophic 2005 Atlantic hurricane that became one of the most intense on record, causing widespread destruction in the Caribbean and the United States.
 E512140 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: Wilma | Statement: [2005 Atlantic hurricane season, retiredStormName, Wilma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wilma
Context triple: [2005 Atlantic hurricane season, retiredStormName, Wilma]
  • A. Vilma
    Vilma is a feminine given name used in various cultures, often as a variant of Wilma or Vilhelmina.
  • B. Yolanda
    Yolanda is a feminine given name used in various cultures, often associated with figures in the arts, activism, and public life.
  • C. Clarita
    Clarita is a Spanish diminutive form of the given name Clara, often used as an affectionate or familiar variant.
  • D. Irma
    Irma is a feminine given name used in various European and Latin American cultures, often considered a variant or related form of names like Emma or Irmina.
  • E. Marla
    Marla is a feminine given name most notably borne by American actress and television personality Marla Maples.
  • 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: Wilma
Triple: [2005 Atlantic hurricane season, retiredStormName, Wilma]
Generated description
Wilma was a catastrophic 2005 Atlantic hurricane that became one of the most intense on record, causing widespread destruction in the Caribbean and the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wilma
Target entity description: Wilma was a catastrophic 2005 Atlantic hurricane that became one of the most intense on record, causing widespread destruction in the Caribbean and the United States.
  • A. Vilma
    Vilma is a feminine given name used in various cultures, often as a variant of Wilma or Vilhelmina.
  • B. Yolanda
    Yolanda is a feminine given name used in various cultures, often associated with figures in the arts, activism, and public life.
  • C. Clarita
    Clarita is a Spanish diminutive form of the given name Clara, often used as an affectionate or familiar variant.
  • D. Irma
    Irma is a feminine given name used in various European and Latin American cultures, often considered a variant or related form of names like Emma or Irmina.
  • E. Marla
    Marla is a feminine given name most notably borne by American actress and television personality Marla Maples.
  • 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_69bd464b07f8819095aa76577c9829e4 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd91aab9348190a373b30bb305f933 completed March 20, 2026, 6:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf18c8db388190a31f55854e7370fc completed March 21, 2026, 10:16 p.m.
NEDg Description generation batch_69bf19c8273081908a5138e9af921ec7 completed March 21, 2026, 10:20 p.m.
NED2 Entity disambiguation (via description) batch_69bf1a3049648190b5040e587671610a completed March 21, 2026, 10:22 p.m.
Created at: March 20, 2026, 2 p.m.