Triple

T15060020
Position Surface form Disambiguated ID Type / Status
Subject Lady Elizabeth Coke E379599 entity
Predicate hasGivenName P17 FINISHED
Object Elizabeth
Elizabeth is a feminine given name of Hebrew origin that has been widely used by royalty and notable figures across history and cultures.
 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: [Lady Elizabeth Coke, hasGivenName, Elizabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Elizabeth
Context triple: [Lady Elizabeth Coke, hasGivenName, Elizabeth]
  • A. Elizabeth
    Elizabeth "Betty" Ford was the influential First Lady of the United States from 1974 to 1977, renowned for her advocacy on women's rights, breast cancer awareness, and addiction treatment.
  • B. Elizabeth
    Elizabeth is the middle name of Diane Elizabeth Dern, an individual likely known in relation to the Dern family.
  • C. Elizabeth
    Elizabeth is the given name of Elizabeth Camilla Julia "Lisl" Godowsky, an individual associated with the Godowsky family.
  • D. Elizabeth
    Elizabeth is the full given name of Betsy McCaughey, an American politician, writer, and former lieutenant governor of New York.
  • E. Elizabeth
    Elizabeth is the given first name of American actress Bess Armstrong, known for her work in film and television since the late 1970s.
  • 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: [Lady Elizabeth Coke, hasGivenName, Elizabeth]
Generated description
Elizabeth is a feminine given name of Hebrew origin that has been widely used by royalty and notable figures across history and cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Elizabeth
Target entity description: Elizabeth is a feminine given name of Hebrew origin that has been widely used by royalty and notable figures across history and cultures.
  • 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 Princess Elizabeth of Yugoslavia, a Yugoslav royal and public figure.
  • C. Elizabeth
    Elizabeth is the given name of Lady Elizabeth Spencer-Churchill, a member of the prominent Spencer-Churchill aristocratic family in Britain.
  • D. Elizabeth
    Elizabeth is the middle name of Princess Beatrice of York, a member of the British royal family.
  • E. Elizabeth
    Elizabeth is the given name of the renowned Victorian-era English poet Elizabeth Barrett Browning.
  • 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69dedee50afc8190bf7b0f4bbe8c60a3 completed April 15, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69fea5a8b3708190be7c35a05fd08a52 completed May 9, 2026, 3:10 a.m.
NEDg Description generation batch_69fea694090c8190a449725dcdd3a37b completed May 9, 2026, 3:14 a.m.
NED2 Entity disambiguation (via description) batch_69fea76e2ff8819099acea30c49bd5ed completed May 9, 2026, 3:18 a.m.
Created at: April 10, 2026, 3:01 a.m.