Triple
T18711731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Woman of Affairs |
E457529
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
John Colton
John Colton was an American playwright and screenwriter known for adapting stage works and crafting screenplays during Hollywood’s early sound era.
|
E1338867
|
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: John Colton | Statement: [A Woman of Affairs, screenwriter, John Colton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Colton Context triple: [A Woman of Affairs, screenwriter, John Colton]
-
A.
Paul Colton
Paul Colton is an Irish Anglican bishop who serves as the Church of Ireland’s Bishop of Cork, Cloyne and Ross.
-
B.
Greg Colton
Greg Colton is an American animation director best known for his work on the television series "Family Guy," including the acclaimed episode "Road to the Multiverse."
-
C.
Colin Whisterfield
Colin Whisterfield is the central protagonist of Alan Garner’s novel "Boneland," whose fragmented memories and search for his missing twin sister drive the book’s blend of psychological drama and mythic fantasy.
-
D.
John Collin
John Collin was a British actor known for his work in film and television during the mid-20th century.
-
E.
John Hampson
John Hampson was the husband of renowned German actress Therese Giehse.
- 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: John Colton Triple: [A Woman of Affairs, screenwriter, John Colton]
Generated description
John Colton was an American playwright and screenwriter known for adapting stage works and crafting screenplays during Hollywood’s early sound era.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Colton Target entity description: John Colton was an American playwright and screenwriter known for adapting stage works and crafting screenplays during Hollywood’s early sound era.
-
A.
Paul Colton
Paul Colton is an Irish Anglican bishop who serves as the Church of Ireland’s Bishop of Cork, Cloyne and Ross.
-
B.
Greg Colton
Greg Colton is an American animation director best known for his work on the television series "Family Guy," including the acclaimed episode "Road to the Multiverse."
-
C.
Colin Whisterfield
Colin Whisterfield is the central protagonist of Alan Garner’s novel "Boneland," whose fragmented memories and search for his missing twin sister drive the book’s blend of psychological drama and mythic fantasy.
-
D.
John Collin
John Collin was a British actor known for his work in film and television during the mid-20th century.
-
E.
John Hampson
John Hampson was the husband of renowned German actress Therese Giehse.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5671c53988190bfc132c853cebd02 |
completed | April 19, 2026, 11:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a052b3f247c8190922c4ce9f67301a0 |
completed | May 14, 2026, 1:54 a.m. |
| NEDg | Description generation | batch_6a052c6373088190a81e53963dac9c6f |
completed | May 14, 2026, 1:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a052d6f1f8081908810e99dff28b586 |
completed | May 14, 2026, 2:03 a.m. |
Created at: April 10, 2026, 11:50 a.m.