Triple
T10178024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Elizabeth Spencer-Churchill |
E235903
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Elizabeth
Elizabeth is the given name of Lady Elizabeth Spencer-Churchill, a member of the prominent Spencer-Churchill aristocratic family in Britain.
|
E844866
|
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 Spencer-Churchill, givenName, Elizabeth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Context triple: [Lady Elizabeth Spencer-Churchill, givenName, Elizabeth]
-
A.
Elizabeth
Elizabeth is the birth name of American actress and singer Betty Hutton, a popular Hollywood star of the 1940s and 1950s.
-
B.
Elizabeth
Elizabeth is the first name of Elizabeth Bishop, the acclaimed American poet known for her precise language and vivid imagery.
-
C.
Elizabeth
Elizabeth was the given name of Elizabeth Batts Cook, the wife of British explorer Captain James Cook.
-
D.
Elizabeth
Elizabeth is a comedic, high-strung fiancée character in the 1974 Mel Brooks film "Young Frankenstein," known for her dramatic personality and memorable scenes.
-
E.
Elizabeth
Elizabeth is the birth name of American actress and comedian Ellie Kemper, known for her roles in "The Office" and "Unbreakable Kimmy Schmidt."
- 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 Spencer-Churchill, givenName, Elizabeth]
Generated description
Elizabeth is the given name of Lady Elizabeth Spencer-Churchill, a member of the prominent Spencer-Churchill aristocratic family in Britain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Target entity description: Elizabeth is the given name of Lady Elizabeth Spencer-Churchill, a member of the prominent Spencer-Churchill aristocratic family in Britain.
-
A.
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.
-
B.
Elizabeth
Elizabeth is the given first name of Lady Sarah McCorquodale, the elder sister of Diana, Princess of Wales.
-
C.
Elizabeth
Elizabeth is the middle name of Lady Sarah Chatto, a British painter and member of the extended royal family.
-
D.
Elizabeth
Elizabeth was the Duchess of York who later became Queen Elizabeth The Queen Mother, a prominent member of the British royal family in the 20th century.
-
E.
Elizabeth
Elizabeth is the given name of the renowned Victorian-era English poet Elizabeth Barrett Browning.
- 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_69ca84d1d5f88190ab878a1021ecff68 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdecd620808190892c6e3074500280 |
completed | April 2, 2026, 4:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d300a40638819082e575d957711377 |
completed | April 6, 2026, 12:39 a.m. |
| NEDg | Description generation | batch_69d30256ee40819098569b37eb27d3d1 |
completed | April 6, 2026, 12:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d302d248e08190b6b7bae9343b6f9a |
completed | April 6, 2026, 12:48 a.m. |
Created at: March 30, 2026, 9:11 p.m.