Triple
T20808484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twin Beds |
E512231
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Arthur Loft |
—
|
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: Arthur Loft | Statement: [Twin Beds, hasCastMember, Arthur Loft]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arthur Loft Context triple: [Twin Beds, hasCastMember, Arthur Loft]
-
A.
Arthur Loft
chosen
Arthur Loft was an American character actor active in the 1930s and 1940s, known for his numerous supporting roles in Hollywood films.
-
B.
Art Croft
Art Croft is a central figure and narrator in the Western novel and film "The Ox-Bow Incident," whose perspective frames the story’s exploration of mob justice and moral responsibility.
-
C.
Edward Ellett
Edward Ellett was an early settler and prominent local figure after whom the town of Ellettsville, Indiana, was named.
-
D.
Philip Watts
Philip Watts was a prominent British naval architect best known for designing major warships for the Royal Navy in the late 19th and early 20th centuries.
-
E.
Sam Fell
Sam Fell is a British film director and animator best known for his work on stop-motion and computer-animated features such as "Flushed Away" and "ParaNorman."
- 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2d0a2a081908fb0e3d890e87aaf |
completed | April 21, 2026, 12:20 a.m. |
Created at: April 16, 2026, 12:40 p.m.