Triple
T14627475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Douglas Bader |
E343388
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Joan Murray |
—
|
NE NERFINISHED |
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: Joan Murray | Statement: [Douglas Bader, spouse, Joan Murray]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joan Murray Context triple: [Douglas Bader, spouse, Joan Murray]
-
A.
Joan Murray
chosen
Joan Murray was the wife of famed British World War II flying ace and double amputee Sir Douglas Bader.
-
B.
Joan Drane
Joan Drane was the wife of American actor Lee Van Cleef, known for his roles in classic Western films.
-
C.
Joan Bolger
Joan Bolger is the wife of former New Zealand Prime Minister Jim Bolger and served as the country's viceregal consort during his term as Governor-General.
-
D.
Joan Craig
Joan Craig is a central character in the 1936 musical comedy film "Three Smart Girls," one of the three sisters whose efforts to reunite their divorced parents drive the story.
-
E.
Joan McCracken
Joan McCracken was an American actress and dancer known for her comic talent and influential work in mid-20th-century Broadway musicals.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4a7c8fc81909d10c1f563d7d1e7 |
completed | April 14, 2026, 9:41 p.m. |
Created at: April 10, 2026, 1:26 a.m.