Triple
T19664250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Green |
E472160
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Caught |
—
|
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: Caught | Statement: [Henry Green, notableWork, Caught]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caught Context triple: [Henry Green, notableWork, Caught]
-
A.
Caught
chosen
Caught is a 1949 film noir melodrama directed by Max Ophüls, known for its dark exploration of marriage, power, and entrapment in postwar American society.
-
B.
Caught
"Caught" is a song by English indie rock band Florence + the Machine from their 2015 album *How Big, How Blue, How Beautiful*.
-
C.
Catch
Catch is a high-end seafood and sushi restaurant known for its stylish atmosphere and celebrity clientele, located within the ARIA Resort & Casino in Las Vegas.
-
D.
Snagged
"Snagged" is a lighthearted mystery novel by Carol Higgins Clark featuring her recurring sleuth Regan Reilly in a humorous whodunit involving murder and mayhem.
-
E.
Trapped
Trapped is a 2002 American thriller film produced by Mandalay Pictures, centered on a family's harrowing kidnapping ordeal and their desperate attempts to outwit their captors.
- 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_69d8e514f2e08190ba70a4449519d218 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6416749d48190b141a6acd20c9694 |
completed | April 20, 2026, 3:08 p.m. |
Created at: April 10, 2026, 1:45 p.m.