Triple

T10155270
Position Surface form Disambiguated ID Type / Status
Subject Elisabeta E232759 entity
Predicate isVariantOf P455 FINISHED
Object Elizabeth
Elizabeth is a classic given name of Hebrew origin, widely used in English-speaking countries and borne by numerous queens, saints, and notable historical figures.
 E40040 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: Elizabeth | Statement: [Elisabeta, isVariantOf, Elizabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Elizabeth
Context triple: [Elisabeta, isVariantOf, Elizabeth]
  • A. Elizabeth
    Elizabeth is the middle name of Lady Sarah Chatto, a British painter and member of the extended royal family.
  • B. Elizabeth
    "Elizabeth" is a popular country and gospel song by The Statler Brothers, known for its rich harmonies and storytelling lyrics.
  • C. Elizabeth
    Elizabeth is the given first name of American silent film actress Betty Bronson, known for her role as Peter Pan in the 1924 film adaptation.
  • D. Elizabeth
    Elizabeth is the central protagonist of the interactive narrative game "If/Then," around whom the story’s key choices and emotional developments revolve.
  • E. Elizabeth
    Elizabeth is the central character in the Broadway musical "If/Then," a woman who explores how a single choice can lead to radically different life paths.
  • 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: Elizabeth
Triple: [Elisabeta, isVariantOf, Elizabeth]
Generated description
Elizabeth is a classic given name of Hebrew origin, widely used in English-speaking countries and borne by numerous queens, saints, and notable historical figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Elizabeth
Target entity description: Elizabeth is a classic given name of Hebrew origin, widely used in English-speaking countries and borne by numerous queens, saints, and notable historical figures.
  • A. Elizabeth chosen
    Elizabeth is a feminine given name of Hebrew origin, traditionally interpreted to mean "God is my oath" and widely used in many English-speaking and European cultures.
  • B. Elizabeth
    Elizabeth is the given name of Lady Elizabeth Spencer-Churchill, a member of the prominent Spencer-Churchill aristocratic family in Britain.
  • C. Elizabeth
    Elizabeth is the given name of the renowned Victorian-era English poet Elizabeth Barrett Browning.
  • D. Elizabeth
    Elizabeth is the given name of Caroline Elizabeth DeWint, a 19th-century figure identifiable by this personal name.
  • E. Elizabeth
    Elizabeth is a biblical figure in the New Testament, known as the mother of John the Baptist and a relative of Mary, the mother of Jesus.
  • F. None of above.

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_69ca84885e48819088a31b127cf44904 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdec3a5e7c819098b2f9ccbde7cf94 completed April 2, 2026, 4:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d3176ac9388190bc76b3cffce93a3d completed April 6, 2026, 2:16 a.m.
NEDg Description generation batch_69d31851a9c481908952592e6362b79f completed April 6, 2026, 2:20 a.m.
NED2 Entity disambiguation (via description) batch_69d318c0cb8081909cfd53e586192ae7 completed April 6, 2026, 2:21 a.m.
Created at: March 30, 2026, 9:09 p.m.