Triple
T10015445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Leeson |
E199479
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Judy Leeson
Judy Leeson is the wife of British actor John Leeson, best known as the voice of K-9 in the classic Doctor Who television series.
|
E835046
|
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: Judy Leeson | Statement: [John Leeson, spouse, Judy Leeson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Judy Leeson Context triple: [John Leeson, spouse, Judy Leeson]
-
A.
Christa Miller
Christa Miller is an American actress best known for her comedic television roles, including prominent parts on series like Scrubs and Cougar Town.
-
B.
Judith Myers
Judith Myers is a character in the Halloween horror franchise, known as Michael Myers' older sister and his first murder victim.
-
C.
Adrienne Ames
Adrienne Ames was an American film actress of the 1930s known for her glamorous screen presence and roles in Hollywood dramas and comedies.
-
D.
Diana Woodward
Diana Woodward is a daughter of renowned American investigative journalist Bob Woodward.
-
E.
Sharon Lepore
Sharon Lepore is known as one of the former wives of famed American television and radio host Larry King.
- 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: Judy Leeson Triple: [John Leeson, spouse, Judy Leeson]
Generated description
Judy Leeson is the wife of British actor John Leeson, best known as the voice of K-9 in the classic Doctor Who television series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Judy Leeson Target entity description: Judy Leeson is the wife of British actor John Leeson, best known as the voice of K-9 in the classic Doctor Who television series.
-
A.
Christa Miller
Christa Miller is an American actress best known for her comedic television roles, including prominent parts on series like Scrubs and Cougar Town.
-
B.
Judith Myers
Judith Myers is a character in the Halloween horror franchise, known as Michael Myers' older sister and his first murder victim.
-
C.
Adrienne Ames
Adrienne Ames was an American film actress of the 1930s known for her glamorous screen presence and roles in Hollywood dramas and comedies.
-
D.
Diana Woodward
Diana Woodward is a daughter of renowned American investigative journalist Bob Woodward.
-
E.
Sharon Lepore
Sharon Lepore is known as one of the former wives of famed American television and radio host Larry King.
- 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_69ca8315a1a08190ab310f25620f362b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd4ad3348190bae03cd37c787674 |
completed | April 2, 2026, 1:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d26a99971081908397f06c0ce913d0 |
completed | April 5, 2026, 1:58 p.m. |
| NEDg | Description generation | batch_69d26c20f50081909a8a3b4530dc5fc0 |
completed | April 5, 2026, 2:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d26caee48481909d085b8df7ce14ab |
completed | April 5, 2026, 2:07 p.m. |
Created at: March 30, 2026, 8:52 p.m.