Triple
T14959399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bess Armstrong |
E373020
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Elizabeth
Elizabeth is the given first name of American actress Bess Armstrong, known for her work in film and television since the late 1970s.
|
E1128956
|
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: [Bess Armstrong, givenName, Elizabeth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Context triple: [Bess Armstrong, givenName, 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 biographical work by J. Randy Taraborrelli that chronicles the life and career of actress Elizabeth Taylor.
-
C.
Elizabeth
Elizabeth is the given name of Caroline Elizabeth DeWint, a 19th-century figure identifiable by this personal name.
-
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: [Bess Armstrong, givenName, Elizabeth]
Generated description
Elizabeth is the given first name of American actress Bess Armstrong, known for her work in film and television since the late 1970s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Target entity description: Elizabeth is the given first name of American actress Bess Armstrong, known for her work in film and television since the late 1970s.
-
A.
Elizabeth
Elizabeth is the birth name of American actress Téa Leoni, known for her roles in film and television such as "Madam Secretary."
-
B.
Elizabeth
Elizabeth is the birth name of American actress, consumer advocate, and television personality Betty Furness.
-
C.
Elizabeth
Elizabeth is the birth name of American actress and television host Busy Philipps, known for her roles in series like "Freaks and Geeks" and "Dawson's Creek."
-
D.
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.
-
E.
Elizabeth
Elizabeth is the birth name of American actress and singer Betty Hutton, a popular Hollywood star of the 1940s and 1950s.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6cd85bc81909040b7ff78f62554 |
completed | April 15, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e8192548190ad268b5804c97060 |
completed | May 9, 2026, 12:23 a.m. |
| NEDg | Description generation | batch_69fe802944848190a4e6e94dc1d9830d |
completed | May 9, 2026, 12:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe80be100481908dcf07b683fc1411 |
completed | May 9, 2026, 12:33 a.m. |
Created at: April 10, 2026, 2:40 a.m.