Triple
T14531320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rex Harrison |
E340920
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Kay Kendall |
E953249
|
NE FINISHED |
How this triple was built (2 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: [Rex Harrison, spouse, Kay Kendall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kay Kendall Context triple: [Rex Harrison, spouse, Kay Kendall]
-
A.
Kay Kendall
chosen
Kay Kendall was a British actress and comedian best known for her sparkling performances in 1950s films and her charismatic screen presence.
-
B.
Kendal Richardson
Kendal Richardson is a political figure who ran for mayor in the 2023 Dallas mayoral election.
-
C.
Kim Aldrich
Kim Aldrich is a central astronaut character in the science fiction horror film "The Last Days on Mars," involved in a doomed mission on the Red Planet.
-
D.
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.
-
E.
Jo Morrow
Jo Morrow is an American actress best known for her film and television roles in the late 1950s and early 1960s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea052d01c81909c8592c351be6f35 |
completed | April 14, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd94acd8288190a91bf09220126e13 |
completed | May 8, 2026, 7:45 a.m. |
Created at: April 10, 2026, 1:22 a.m.