Triple

T14991693
Position Surface form Disambiguated ID Type / Status
Subject Debra E373849 entity
Predicate hasDiminutive P456 FINISHED
Object Debby
Debby is a feminine given name commonly used as a diminutive form of Deborah or Debra.
 E1132342 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: Debby | Statement: [Debra, hasDiminutive, Debby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Debby
Context triple: [Debra, hasDiminutive, Debby]
  • A. Yolanda
    Yolanda is a feminine given name used in various cultures, often associated with figures in the arts, activism, and public life.
  • B. 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.
  • C. 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.
  • D. Hurricane Hank
    Hurricane Hank was the nickname of Henry Armstrong, a legendary American boxer renowned for simultaneously holding world titles in three different weight divisions.
  • E. Vilma
    Vilma is a feminine given name used in various cultures, often as a variant of Wilma or Vilhelmina.
  • 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: Debby
Triple: [Debra, hasDiminutive, Debby]
Generated description
Debby is a feminine given name commonly used as a diminutive form of Deborah or Debra.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Debby
Target entity description: Debby is a feminine given name commonly used as a diminutive form of Deborah or Debra.
  • A. Yolanda
    Yolanda is a feminine given name used in various cultures, often associated with figures in the arts, activism, and public life.
  • B. 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.
  • C. 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.
  • D. Hurricane Hank
    Hurricane Hank was the nickname of Henry Armstrong, a legendary American boxer renowned for simultaneously holding world titles in three different weight divisions.
  • E. Vilma
    Vilma is a feminine given name used in various cultures, often as a variant of Wilma or Vilhelmina.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded715db408190b44e8a8452c79764 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe969842848190a030db797c851fed completed May 9, 2026, 2:06 a.m.
NEDg Description generation batch_69fe983820f88190843361b0ac391d38 completed May 9, 2026, 2:13 a.m.
NED2 Entity disambiguation (via description) batch_69fe98b18ab48190b2a47418904e6643 completed May 9, 2026, 2:15 a.m.
Created at: April 10, 2026, 2:53 a.m.