Triple
T3430650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica Tandy |
E72327
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Jack Hawkins |
E145577
|
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: Jack Hawkins | Statement: [Jessica Tandy, spouse, Jack Hawkins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jack Hawkins Context triple: [Jessica Tandy, spouse, Jack Hawkins]
-
A.
Jack Hawkins
chosen
Jack Hawkins was a distinguished British actor known for his commanding presence in mid-20th-century war and historical films.
-
B.
Trevor Howard
Trevor Howard was a distinguished English film and stage actor best known for his roles in classic films such as "Brief Encounter" and "The Third Man."
-
C.
Michael Wilding
Michael Wilding was a British film and stage actor best known for his roles in 1940s–1950s British cinema and for his high-profile marriage to actress Elizabeth Taylor.
-
D.
George Powell
George Powell was a 19th-century British sealer and explorer noted for his Antarctic voyages and co-discovery of several sub-Antarctic islands.
-
E.
Jack Cardiff
Jack Cardiff was an acclaimed British cinematographer and director renowned for his pioneering use of Technicolor and visually striking work on classic films.
- 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_69ad85ae14308190bcbc25cfa0246c0b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9bd61908190a7bdd01f24334fc3 |
completed | March 8, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4881f1e1c81908de3a0729761c4f7 |
completed | March 13, 2026, 9:56 p.m. |
Created at: March 8, 2026, 3:15 p.m.