Triple
T11871545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Girls |
E282417
|
entity |
| Predicate | starredActor |
P5563
|
FINISHED |
| Object |
Kay Kendall
Kay Kendall was a British actress and comedian best known for her sparkling performances in 1950s films and her charismatic screen presence.
|
E953249
|
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: Kay Kendall | Statement: [Les Girls, starredActor, Kay Kendall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kay Kendall Context triple: [Les Girls, starredActor, Kay Kendall]
-
A.
Kendal Richardson
Kendal Richardson is a political figure who ran for mayor in the 2023 Dallas mayoral election.
-
B.
Kay Walsh
Kay Walsh was a British actress and dancer known for her versatile performances in mid-20th-century cinema and her collaborations with prominent directors like David Lean.
-
C.
Jo Morrow
Jo Morrow is an American actress best known for her film and television roles in the late 1950s and early 1960s.
-
D.
Darby Hickson
Darby Hickson is the former wife of American Republican political strategist and commentator Karl Rove.
-
E.
Dana York
Dana York is an American woman best known as the widow of rock musician Tom Petty, whom she married in 2001 and remained with until his death.
- 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: Kay Kendall Triple: [Les Girls, starredActor, Kay Kendall]
Generated description
Kay Kendall was a British actress and comedian best known for her sparkling performances in 1950s films and her charismatic screen presence.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kay Kendall Target entity description: Kay Kendall was a British actress and comedian best known for her sparkling performances in 1950s films and her charismatic screen presence.
-
A.
Kendal Richardson
Kendal Richardson is a political figure who ran for mayor in the 2023 Dallas mayoral election.
-
B.
Kay Walsh
Kay Walsh was a British actress and dancer known for her versatile performances in mid-20th-century cinema and her collaborations with prominent directors like David Lean.
-
C.
Jo Morrow
Jo Morrow is an American actress best known for her film and television roles in the late 1950s and early 1960s.
-
D.
Darby Hickson
Darby Hickson is the former wife of American Republican political strategist and commentator Karl Rove.
-
E.
Dana York
Dana York is an American woman best known as the widow of rock musician Tom Petty, whom she married in 2001 and remained with until his death.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8be18b7d48190b7fb1c3a67a891ed |
completed | April 10, 2026, 9:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f417bb131c8190b0923e077cca74be |
completed | May 1, 2026, 3:02 a.m. |
| NEDg | Description generation | batch_69f41f8d297c81908cfe60b10989e550 |
completed | May 1, 2026, 3:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f422778a10819093bc2473ef30fe71 |
completed | May 1, 2026, 3:48 a.m. |
Created at: April 8, 2026, 9:43 p.m.