Triple
T3192388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albert Finney |
E66852
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Jane Wenham
Jane Wenham was a British actress known for her work in mid-20th-century film, television, and theatre.
|
E346219
|
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: Jane Wenham | Statement: [Albert Finney, spouse, Jane Wenham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jane Wenham Context triple: [Albert Finney, spouse, Jane Wenham]
-
A.
Tessa Menzies
Tessa Menzies is a child of California politician and governor Gavin Newsom.
-
B.
Saskia Reeves
Saskia Reeves is a British actress known for her work in film, television, and theatre, including roles in series such as "Luther" and numerous acclaimed stage productions.
-
C.
Rose Leslie
Rose Leslie is a Scottish actress best known for her roles in the TV series "Game of Thrones" and "Downton Abbey," as well as various film and television projects.
-
D.
Lara Pulver
Lara Pulver is a British actress known for her roles in television series such as "Sherlock" and "Spooks," as well as various film and stage productions.
-
E.
Margot Tennant
Margot Tennant, later Margot Asquith, was a prominent British socialite, author, and wit who became the influential second wife of Prime Minister H. H. Asquith.
- 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: Jane Wenham Triple: [Albert Finney, spouse, Jane Wenham]
Generated description
Jane Wenham was a British actress known for her work in mid-20th-century film, television, and theatre.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jane Wenham Target entity description: Jane Wenham was a British actress known for her work in mid-20th-century film, television, and theatre.
-
A.
Tessa Menzies
Tessa Menzies is a child of California politician and governor Gavin Newsom.
-
B.
Saskia Reeves
Saskia Reeves is a British actress known for her work in film, television, and theatre, including roles in series such as "Luther" and numerous acclaimed stage productions.
-
C.
Rose Leslie
Rose Leslie is a Scottish actress best known for her roles in the TV series "Game of Thrones" and "Downton Abbey," as well as various film and television projects.
-
D.
Lara Pulver
Lara Pulver is a British actress known for her roles in television series such as "Sherlock" and "Spooks," as well as various film and stage productions.
-
E.
Margot Tennant
Margot Tennant, later Margot Asquith, was a prominent British socialite, author, and wit who became the influential second wife of Prime Minister H. H. Asquith.
- 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_69ad8588ba18819086a10951c32ecb80 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6e8e4b48190bc7c6443fc6da900 |
completed | March 8, 2026, 4:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3b7e5c48190a8fc84ae78d4bd66 |
completed | March 12, 2026, 5:11 p.m. |
| NEDg | Description generation | batch_69b2fa0ed27c8190a32c153b44b7b2dd |
completed | March 12, 2026, 5:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b312b273b48190a949e61b87722084 |
completed | March 12, 2026, 7:23 p.m. |
Created at: March 8, 2026, 3:07 p.m.