Triple
T20870607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hope Lange |
E513879
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Don 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: Don Murray | Statement: [Hope Lange, spouse, Don Murray]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Murray Context triple: [Hope Lange, spouse, Don Murray]
-
A.
Don Murray
chosen
Don Murray is an American actor best known for his Oscar-nominated film debut in the 1956 drama "Bus Stop" opposite Marilyn Monroe.
-
B.
Ken Morrow
Ken Morrow is an American former defenseman best known for winning gold with the "Miracle on Ice" 1980 U.S. Olympic hockey team and then capturing four consecutive Stanley Cups with the New York Islanders.
-
C.
Luke Murray
Luke Murray is an American basketball coach known for his assistant coaching roles at several major college programs and as the son of actor Bill Murray.
-
D.
Ian Dunn
Ian Dunn is a British actor known for his work in television, film, and theatre, and for being married to the late actress Emma Chambers.
-
E.
Ed McHugh
Ed McHugh is a relative of American character actor Frank McHugh, who was known for his prolific work in early 20th-century film and theater.
- 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_69e0b4f675cc8190b4e745225b62eb66 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c4637ec48190830023d20fb8124c |
completed | April 21, 2026, 12:27 a.m. |
Created at: April 16, 2026, 12:45 p.m.