Triple
T5271108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betty Hutton |
E119259
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Elizabeth
Elizabeth is the birth name of American actress and singer Betty Hutton, a popular Hollywood star of the 1940s and 1950s.
|
E508770
|
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: [Betty Hutton, givenName, Elizabeth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Context triple: [Betty Hutton, 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 the middle name of Lady Sarah Chatto, a British painter and member of the extended royal family.
-
D.
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.
-
E.
Elizabeth
Elizabeth is the given name of the renowned Victorian-era English poet Elizabeth Barrett Browning.
- 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: [Betty Hutton, givenName, Elizabeth]
Generated description
Elizabeth is the birth name of American actress and singer Betty Hutton, a popular Hollywood star of the 1940s and 1950s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Target entity description: Elizabeth is the birth name of American actress and singer Betty Hutton, a popular Hollywood star of the 1940s and 1950s.
-
A.
Elizabeth
Elizabeth is the birth name of American comedian, writer, and actress Tina Fey, known for her work on "Saturday Night Live" and "30 Rock."
-
B.
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.
-
C.
Elizabeth
Elizabeth is the first name of Elizabeth Warren, a prominent American politician and U.S. senator from Massachusetts known for her work on consumer protection and economic inequality.
-
D.
Elizabeth
Elizabeth is the full first name of Liz Lemon, the fictional television writer and main character from the comedy series "30 Rock."
-
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_69bd446c38e081908cdaf113bdf86790 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7c1fa01081909d589686289b624b |
completed | March 20, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf06cb5f788190b9ee79ca15da9d58 |
completed | March 21, 2026, 8:59 p.m. |
| NEDg | Description generation | batch_69bf08e009788190ae74e25f35ccf100 |
completed | March 21, 2026, 9:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf0979c11c8190bc5c3957d098d8d5 |
completed | March 21, 2026, 9:11 p.m. |
Created at: March 20, 2026, 1:51 p.m.