Triple
T13519431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Fine Romance |
E322853
|
entity |
| Predicate | hasMainCharacter |
P1183
|
FINISHED |
| Object |
Laura Dalton
Laura Dalton is the central protagonist of the British sitcom "A Fine Romance," around whose romantic and personal life the series revolves.
|
E1079044
|
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: Laura Dalton | Statement: [A Fine Romance, hasMainCharacter, Laura Dalton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laura Dalton Context triple: [A Fine Romance, hasMainCharacter, Laura Dalton]
-
A.
Laura Davenport
Laura Davenport is the daughter of English actor Nigel Davenport.
-
B.
Laura Harrington
Laura Harrington is an American actress best known for her role in the 1986 Stephen King film "Maximum Overdrive."
-
C.
Jessica Daly
Jessica Daly is the wife of former Irish rugby union star and coach Ronan O'Gara.
-
D.
Laura Jones
Laura Jones is an Australian screenwriter known for her work on acclaimed films such as "High Tide" (1987) and several literary adaptations.
-
E.
Audrey Dalton
Audrey Dalton is an Irish-born actress best known for her roles in 1950s Hollywood films and television, including a prominent part in the 1953 drama "Titanic."
- 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: Laura Dalton Triple: [A Fine Romance, hasMainCharacter, Laura Dalton]
Generated description
Laura Dalton is the central protagonist of the British sitcom "A Fine Romance," around whose romantic and personal life the series revolves.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laura Dalton Target entity description: Laura Dalton is the central protagonist of the British sitcom "A Fine Romance," around whose romantic and personal life the series revolves.
-
A.
Laura Davenport
Laura Davenport is the daughter of English actor Nigel Davenport.
-
B.
Laura Harrington
Laura Harrington is an American actress best known for her role in the 1986 Stephen King film "Maximum Overdrive."
-
C.
Jessica Daly
Jessica Daly is the wife of former Irish rugby union star and coach Ronan O'Gara.
-
D.
Laura Jones
Laura Jones is an Australian screenwriter known for her work on acclaimed films such as "High Tide" (1987) and several literary adaptations.
-
E.
Audrey Dalton
Audrey Dalton is an Irish-born actress best known for her roles in 1950s Hollywood films and television, including a prominent part in the 1953 drama "Titanic."
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa27f048190bed33a98e28c8d09 |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd08698e0819084f3098d471e7dc9 |
completed | May 7, 2026, 5:48 p.m. |
| NEDg | Description generation | batch_69fcd176632c8190aa7dee337688b043 |
completed | May 7, 2026, 5:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fcd28c1f0c819083b934a6afd656bf |
completed | May 7, 2026, 5:57 p.m. |
Created at: April 9, 2026, 9:44 p.m.