Triple
T5590636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Unsinkable Molly Brown |
E146867
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Jack Kruschen |
E301996
|
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 Kruschen | Statement: [The Unsinkable Molly Brown, stars, Jack Kruschen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jack Kruschen Context triple: [The Unsinkable Molly Brown, stars, Jack Kruschen]
-
A.
Jack Kruschen
chosen
Jack Kruschen was a Canadian-born character actor known for his prolific work in film, television, and radio, including an Oscar-nominated role in "The Apartment" (1960).
-
B.
Craig Krampf
Craig Krampf is an American drummer and percussionist best known for his session work with prominent rock and pop artists in the 1970s and 1980s.
-
C.
Jack Roth
Jack Roth is a British actor known for his roles in film and television, and is the son of acclaimed actor Tim Roth.
-
D.
Fred Schuler
Fred Schuler is a cinematographer best known for his work on films such as the 1980 comedy "Stir Crazy."
-
E.
Jay Keyser
Jay Keyser is an American linguist known for his influential work in generative phonology and syntax, as well as his long career as a professor at MIT.
- 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020a1d4cc8190a52264dfba6aa011 |
completed | March 22, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c097c85fa481909dc6dcfccce8efa8 |
completed | March 23, 2026, 1:30 a.m. |
Created at: March 22, 2026, 3:38 p.m.