Triple
T21313260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leon Askin |
E525397
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | One, Two, Three |
—
|
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: One, Two, Three | Statement: [Leon Askin, appearedIn, One, Two, Three]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: One, Two, Three Context triple: [Leon Askin, appearedIn, One, Two, Three]
-
A.
One, Two, Three
chosen
One, Two, Three is a 1961 fast-paced Cold War comedy film set in West Berlin, known for its rapid-fire dialogue and satirical take on East–West tensions.
-
B.
One Two
One Two is a small-time London criminal and the central protagonist in Guy Ritchie's crime film "RocknRolla."
-
C.
Count to Three
"Count to Three" is a song by the American rock band Emo, known for its emotionally charged lyrics and melodic instrumentation.
-
D.
Three and One
"Three and One" is a jazz composition by trumpeter and bandleader Thad Jones, recognized as one of his signature works in the modern big band repertoire.
-
E.
1-2-3
1-2-3 is a punk rock song by The Professionals, known for its driving energy and classic early-1980s UK punk sound.
- 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_69e0b518b8948190ad69cf9a8784d397 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e75dcc6350819093763632b7e6e4ac |
completed | April 21, 2026, 11:21 a.m. |
Created at: April 16, 2026, 4:27 p.m.