Triple
T15911297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tipper Gore |
E385853
|
entity |
| Predicate | middleName |
P143
|
FINISHED |
| Object |
Elizabeth
Elizabeth is the middle name of Tipper Gore, the American social issues advocate and former Second Lady of the United States.
|
E1183031
|
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: [Tipper Gore, middleName, Elizabeth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Context triple: [Tipper Gore, middleName, Elizabeth]
-
A.
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.
-
B.
Elizabeth
Elizabeth is a central character in the 1931 horror film "Frankenstein," serving as Henry Frankenstein’s fiancée and a key figure whose vulnerability heightens the story’s emotional and dramatic stakes.
-
C.
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.
-
D.
Elizabeth
Elizabeth is the given name of Elizabeth Jane Cochrane, better known as pioneering American investigative journalist Nellie Bly.
-
E.
Elizabeth
Elizabeth of Denmark was a 16th-century Danish princess who became Electress of Brandenburg through her marriage to Joachim II Hector.
- 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: [Tipper Gore, middleName, Elizabeth]
Generated description
Elizabeth is the middle name of Tipper Gore, the American social issues advocate and former Second Lady of the United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Target entity description: Elizabeth is the middle name of Tipper Gore, the American social issues advocate and former Second Lady of the United States.
-
A.
Elizabeth
Elizabeth is the middle name of Ida Stover Eisenhower, the mother of U.S. President Dwight D. Eisenhower.
-
B.
Elizabeth
Elizabeth is the middle name of Susan Ford, the daughter of former U.S. President Gerald Ford and First Lady Betty Ford.
-
C.
Elizabeth
Elizabeth is the middle name of Lady Louise Windsor, a member of the British royal family and granddaughter of Queen Elizabeth II.
-
D.
Elizabeth
Elizabeth is the middle name of Princess Beatrice of York, a member of the British royal family.
-
E.
Elizabeth
Elizabeth is the middle name of Lucy Elizabeth Jefferson, a member of the Jefferson family associated with early American history.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1565f621c8190a52cda28237610e8 |
completed | April 16, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb04b55ec8190a5b3513b2afa4f83 |
completed | May 9, 2026, 10:08 p.m. |
| NEDg | Description generation | batch_69ffb13fdb6c819091c3ee5c1f199031 |
completed | May 9, 2026, 10:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb208aef881909b3a00e0015c27df |
completed | May 9, 2026, 10:15 p.m. |
Created at: April 10, 2026, 4:52 a.m.