Triple

T71944
Position Surface form Disambiguated ID Type / Status
Subject Kimberly Guilfoyle E1439 entity
Predicate givenName P17 FINISHED
Object Kimberly
Kimberly is a feminine given name of English origin that has been widely used in the United States since the mid-20th century.
 E23752 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: Kimberly | Statement: [Kimberly Guilfoyle, givenName, Kimberly]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kimberly
Context triple: [Kimberly Guilfoyle, givenName, Kimberly]
  • A. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • B. Kathy
    Kathy is the given name of Kathy Hochul, the 57th governor of New York and the first woman to hold that office.
  • C. Rita
    Rita is a feminine given name used in various cultures, often as a short form of names like Margarita.
  • D. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • E. Angela
    Angela is the given name of Angela Merkel, the long-serving former Chancellor of Germany and a prominent European political leader.
  • 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: Kimberly
Triple: [Kimberly Guilfoyle, givenName, Kimberly]
Generated description
Kimberly is a feminine given name of English origin that has been widely used in the United States since the mid-20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kimberly
Target entity description: Kimberly is a feminine given name of English origin that has been widely used in the United States since the mid-20th century.
  • A. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • B. Kathy
    Kathy is the given name of Kathy Hochul, the 57th governor of New York and the first woman to hold that office.
  • C. Rita
    Rita is a feminine given name used in various cultures, often as a short form of names like Margarita.
  • D. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • E. Angela
    Angela is the given name of Angela Merkel, the long-serving former Chancellor of Germany and a prominent European political leader.
  • 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_69a24c06b3bc8190aa4ac89026115efc completed Feb. 28, 2026, 1:59 a.m.
NER Named-entity recognition batch_69a24f190d5481909ac8252867242341 completed Feb. 28, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69a302803f50819081a480c33f08b68a completed Feb. 28, 2026, 2:58 p.m.
NEDg Description generation batch_69a30336ab2881908899f75c76b0d010 completed Feb. 28, 2026, 3:01 p.m.
NED2 Entity disambiguation (via description) batch_69a303c507e08190b60abbb1740721b8 completed Feb. 28, 2026, 3:03 p.m.
Created at: Feb. 28, 2026, 2:03 a.m.