Triple
T711064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Cleese |
E14206
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Jennifer Wade
Jennifer Wade is a British jewelry designer and former model best known as the fourth wife of comedian and actor John Cleese.
|
E203180
|
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: Jennifer Wade | Statement: [John Cleese, spouse, Jennifer Wade]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jennifer Wade Context triple: [John Cleese, spouse, Jennifer Wade]
-
A.
Tahnee Welch
Tahnee Welch is an American actress and model best known for her role in the science-fiction film "Cocoon" and for being the daughter of actress Raquel Welch.
-
B.
Jennifer Williams
Jennifer Williams is known as the daughter of acclaimed American composer and conductor John Williams.
-
C.
Amanda Clifton
Amanda Clifton is an American sports executive and advocate best known as the wife of WNBA star Elena Delle Donne and for her work promoting women’s basketball and LGBTQ+ visibility.
-
D.
Lindsay Brunnock
Lindsay Brunnock is a British art director known for her work in film and television and for being married to actor and director Kenneth Branagh.
-
E.
Amanda Clayton
Amanda Clayton is an American actress best known for her role in the crime drama television series "City on a Hill."
- 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: Jennifer Wade Triple: [John Cleese, spouse, Jennifer Wade]
Generated description
Jennifer Wade is a British jewelry designer and former model best known as the fourth wife of comedian and actor John Cleese.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jennifer Wade Target entity description: Jennifer Wade is a British jewelry designer and former model best known as the fourth wife of comedian and actor John Cleese.
-
A.
Tahnee Welch
Tahnee Welch is an American actress and model best known for her role in the science-fiction film "Cocoon" and for being the daughter of actress Raquel Welch.
-
B.
Jennifer Williams
Jennifer Williams is known as the daughter of acclaimed American composer and conductor John Williams.
-
C.
Amanda Clifton
Amanda Clifton is an American sports executive and advocate best known as the wife of WNBA star Elena Delle Donne and for her work promoting women’s basketball and LGBTQ+ visibility.
-
D.
Lindsay Brunnock
Lindsay Brunnock is a British art director known for her work in film and television and for being married to actor and director Kenneth Branagh.
-
E.
Amanda Clayton
Amanda Clayton is an American actress best known for her role in the crime drama television series "City on a Hill."
- 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a55c99fc8190941c5fd18551792a |
completed | March 1, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adbf2ffb088190a49686609d7de213 |
completed | March 8, 2026, 6:25 p.m. |
| NEDg | Description generation | batch_69adbff135188190908058a2e2d41a1e |
completed | March 8, 2026, 6:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adc0832cd881909702f380412702d5 |
completed | March 8, 2026, 6:31 p.m. |
Created at: March 1, 2026, 7:36 p.m.