Triple
T8546522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wesley Pegden |
E202339
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object |
Glenda Wilkinson
Glenda Wilkinson is a relative of mathematician and probability theorist Wesley Pegden.
|
E763464
|
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: Glenda Wilkinson | Statement: [Wesley Pegden, hasRelative, Glenda Wilkinson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glenda Wilkinson Context triple: [Wesley Pegden, hasRelative, Glenda Wilkinson]
-
A.
Lorraine Adie
Lorraine Adie was a Scottish archaeologist and the mother of drummer and composer Stewart Copeland.
-
B.
Glenda May Jackson
Glenda May Jackson was an acclaimed English actress and Labour Party politician, renowned for her Oscar-winning film performances and later service as a Member of Parliament.
-
C.
Lara Bingle
Lara Bingle is an Australian model, media personality, and entrepreneur best known for her high-profile advertising campaigns and reality television appearances.
-
D.
Renée Asherson
Renée Asherson was a British stage and film actress known for her delicate, expressive performances in mid-20th-century British cinema and theatre.
-
E.
Lesley Sharp
Lesley Sharp is an English actress known for her work in television, film, and theatre, including prominent roles in series such as "Scott & Bailey" and "Afterlife."
- 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: Glenda Wilkinson Triple: [Wesley Pegden, hasRelative, Glenda Wilkinson]
Generated description
Glenda Wilkinson is a relative of mathematician and probability theorist Wesley Pegden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Glenda Wilkinson Target entity description: Glenda Wilkinson is a relative of mathematician and probability theorist Wesley Pegden.
-
A.
Lorraine Adie
Lorraine Adie was a Scottish archaeologist and the mother of drummer and composer Stewart Copeland.
-
B.
Glenda May Jackson
Glenda May Jackson was an acclaimed English actress and Labour Party politician, renowned for her Oscar-winning film performances and later service as a Member of Parliament.
-
C.
Lara Bingle
Lara Bingle is an Australian model, media personality, and entrepreneur best known for her high-profile advertising campaigns and reality television appearances.
-
D.
Renée Asherson
Renée Asherson was a British stage and film actress known for her delicate, expressive performances in mid-20th-century British cinema and theatre.
-
E.
Lesley Sharp
Lesley Sharp is an English actress known for her work in television, film, and theatre, including prominent roles in series such as "Scott & Bailey" and "Afterlife."
- 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_69ca832461e88190a654c5e44e233aa8 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe7511f8c819083d69fb6a0b55801 |
completed | March 31, 2026, 3:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf9ffe17e481908516d2f526d60684 |
completed | April 3, 2026, 11:09 a.m. |
| NEDg | Description generation | batch_69cfa3ca78848190a8e44a2419d1eccd |
completed | April 3, 2026, 11:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfa4203f7c819084d27a53928812cd |
completed | April 3, 2026, 11:27 a.m. |
Created at: March 30, 2026, 6:19 p.m.