Triple
T18830582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard Hawks |
E460516
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Nancy Gross |
—
|
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: Nancy Gross | Statement: [Howard Hawks, spouse, Nancy Gross]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nancy Gross Context triple: [Howard Hawks, spouse, Nancy Gross]
-
A.
Nancy Gross
chosen
Nancy Gross was the wife of renowned American film director Howard Hawks.
-
B.
Nancy Dolman
Nancy Dolman was a Canadian comedic actress and singer best known for her work on the television series "Soap" and for her long marriage to comedian Martin Short.
-
C.
Nancy Kruse
Nancy Kruse is a writer known for her work on the story of the animated film "Encanto."
-
D.
Nancy Goodman
Nancy Goodman is an American diplomat, businesswoman, and philanthropist best known for founding the Susan G. Komen Breast Cancer Foundation.
-
E.
Nancy Walters
Nancy Walters was an American model and film and television actress active in the 1950s and early 1960s, known for roles in Hollywood productions including the Elvis Presley musical "Blue Hawaii."
- 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a9992bb081908ba517a5c9d93ef3 |
completed | April 20, 2026, 4:20 a.m. |
Created at: April 10, 2026, 11:56 a.m.