Triple

T2883796
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth Barrett Browning E59458 entity
Predicate givenName P17 FINISHED
Object Elizabeth
Elizabeth is the given name of the renowned Victorian-era English poet Elizabeth Barrett Browning.
 E307144 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: [Elizabeth Barrett Browning, givenName, Elizabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Elizabeth
Context triple: [Elizabeth Barrett Browning, givenName, Elizabeth]
  • A. Elizabeth
    Elizabeth is the formal first name of Bess Truman, who served as First Lady of the United States as the wife of President Harry S. Truman.
  • B. Elizabeth
    "Elizabeth" is a 1998 historical drama film that chronicles the early reign of Queen Elizabeth I of England, starring Cate Blanchett in the title role.
  • C. Elizabeth
    Elizabeth is a key character in Nathaniel Hawthorne’s short story “The Minister’s Black Veil,” serving as Reverend Hooper’s fiancée whose reaction to his mysterious veil highlights themes of isolation and the fear of hidden sin.
  • D. Elizabeth
    Elizabeth is the middle name of Lady Sarah Chatto, a British painter and member of the extended royal family.
  • E. Elizabeth
    Elizabeth is the given name of Princess Alexandra, The Honourable Lady Ogilvy, a member of the British royal family and cousin of Queen Elizabeth II.
  • 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: [Elizabeth Barrett Browning, givenName, Elizabeth]
Generated description
Elizabeth is the given name of the renowned Victorian-era English poet Elizabeth Barrett Browning.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Elizabeth
Target entity description: Elizabeth is the given name of the renowned Victorian-era English poet Elizabeth Barrett Browning.
  • 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 feminine given name of Hebrew origin, traditionally interpreted to mean "God is my oath" and widely used in many English-speaking and European cultures.
  • C. Elizabeth
    Elizabeth is the given name of Princess Alexandra, The Honourable Lady Ogilvy, a member of the British royal family and cousin of Queen Elizabeth II.
  • D. Elizabeth
    Elizabeth is the formal first name of Bess Truman, who served as First Lady of the United States as the wife of President Harry S. Truman.
  • E. Elizabeth
    "Elizabeth" is a 1998 historical drama film that chronicles the early reign of Queen Elizabeth I of England, starring Cate Blanchett in the title role.
  • 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_69ab4ac739188190a112f42a5a69c951 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abe02e0ec48190b969ed921d179560 completed March 7, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0314baa408190b1b398dcfaa29c53 completed March 10, 2026, 2:57 p.m.
NEDg Description generation batch_69b0351dc18c8190bcd047ccabaa47bc completed March 10, 2026, 3:13 p.m.
NED2 Entity disambiguation (via description) batch_69b035ce3f8481908673a072eb2e6dcd completed March 10, 2026, 3:16 p.m.
Created at: March 6, 2026, 10:03 p.m.