Triple

T22931731
Position Surface form Disambiguated ID Type / Status
Subject Isabella E569457 entity
Predicate hasRelatedName P3889 FINISHED
Object Elizabeth
Elizabeth is a classic given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures, including queens and saints.
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: [Isabella, hasRelatedName, Elizabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elizabeth
Context triple: [Isabella, hasRelatedName, Elizabeth]
  • A. Elizabeth
    Elizabeth is the middle name of Diane Elizabeth Dern, an individual likely known in relation to the Dern family.
  • B. Elizabeth
    Elizabeth is the birth name of American actress and singer Betty Hutton, a popular Hollywood star of the 1940s and 1950s.
  • 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 middle name of Princess Beatrice of York, a member of the British royal family.
  • E. Elizabeth
    Elizabeth is the full given name of Betsy McCaughey, an American politician, writer, and former lieutenant governor of New York.
  • 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: [Isabella, hasRelatedName, Elizabeth]
Generated description
Elizabeth is a classic given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures, including queens and saints.
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 historical and contemporary figures, including queens and saints.
  • 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 was the birth name of Princess Elizabeth of England, who later became Queen Elizabeth I, the influential Tudor monarch of England.
  • C. Elizabeth
    Elizabeth is the middle name of Matilda Elizabeth Frelinghuysen Davis, reflecting a traditional given name of English origin.
  • D. Elizabeth
    Elizabeth is the middle name of Mary Elizabeth Horsley, likely reflecting a traditional English given name.
  • 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_69e2458f7d008190901dccbaebeaba24 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1813260608190bb9e1ca704c7e12f completed April 29, 2026, 3:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0bd3651c408190a2dc8e55d002a496 completed May 19, 2026, 3:05 a.m.
NEDg Description generation batch_6a0bd48cac988190b98142d009a64f54 completed May 19, 2026, 3:10 a.m.
NED2 Entity disambiguation (via description) batch_6a0bd4e53024819084592e995cc902e7 completed May 19, 2026, 3:11 a.m.
Created at: April 17, 2026, 3:44 p.m.