Triple

T1917050
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth E40040 entity
Predicate hasVariant P455 FINISHED
Object Elsie
Elsie is a feminine given name, originally a diminutive of Elizabeth, that has become a standalone name in its own right.
 E214702 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: Elsie | Statement: [Elizabeth, hasVariant, Elsie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Elsie
Context triple: [Elizabeth, hasVariant, Elsie]
  • A. Elsie
    Elsie is a fictional character from the post-apocalyptic virtual reality game "After the Fall."
  • B. Elsie
    Elsie is the internal codename Apple used for the Macintosh LC personal computer during its development.
  • C. Mollie
    Mollie is a young girl in Enid Blyton's "The Wishing-Chair" series who, along with her brother Peter, goes on magical adventures using a flying wishing-chair.
  • D. Martha
    Martha is a feminine given name of Aramaic origin, historically borne by notable figures such as Martha Washington, the first First Lady of the United States.
  • E. Phyllis
    Phyllis is a 1970s American television sitcom, spun off from The Mary Tyler Moore Show, that stars Cloris Leachman as the widowed Phyllis Lindstrom starting a new life in San Francisco.
  • 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: Elsie
Triple: [Elizabeth, hasVariant, Elsie]
Generated description
Elsie is a feminine given name, originally a diminutive of Elizabeth, that has become a standalone name in its own right.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Elsie
Target entity description: Elsie is a feminine given name, originally a diminutive of Elizabeth, that has become a standalone name in its own right.
  • A. Elsie
    Elsie is a fictional character from the post-apocalyptic virtual reality game "After the Fall."
  • B. Elsie
    Elsie is the internal codename Apple used for the Macintosh LC personal computer during its development.
  • C. Mollie
    Mollie is a young girl in Enid Blyton's "The Wishing-Chair" series who, along with her brother Peter, goes on magical adventures using a flying wishing-chair.
  • D. Martha
    Martha is a feminine given name of Aramaic origin, historically borne by notable figures such as Martha Washington, the first First Lady of the United States.
  • E. Phyllis
    Phyllis is a 1970s American television sitcom, spun off from The Mary Tyler Moore Show, that stars Cloris Leachman as the widowed Phyllis Lindstrom starting a new life in San Francisco.
  • 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_69a8864298748190a2f2fd34f7ef8d77 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb20f54848190b9457e1231aa49db completed March 7, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3dcc288819096855351a0e69069 completed March 8, 2026, 10:10 p.m.
NEDg Description generation batch_69adf471909881909de20d9d1fa0b372 completed March 8, 2026, 10:13 p.m.
NED2 Entity disambiguation (via description) batch_69adf50b17a081909b93ad3e08c71772 completed March 8, 2026, 10:15 p.m.
Created at: March 4, 2026, 7:35 p.m.