Triple
T37297130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bugs Bunny/Road Runner Movie |
E925834
|
entity |
| Predicate | featuresFramingSegments |
P38807
|
FINISHED |
| Object | new animation with Bugs Bunny in his home |
—
|
LITERAL 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: new animation with Bugs Bunny in his home | Statement: [The Bugs Bunny/Road Runner Movie, featuresFramingSegments, new animation with Bugs Bunny in his home]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresFramingSegments Context triple: [The Bugs Bunny/Road Runner Movie, featuresFramingSegments, new animation with Bugs Bunny in his home]
-
A.
featuresSegment
chosen
Indicates that one entity includes or highlights a particular segment or portion of another entity as a notable part of it.
-
B.
frame
Indicates placing or presenting something within a particular context, structure, or perspective that shapes how it is interpreted.
-
C.
framesAs
Indicates how one entity presents, characterizes, or interprets another entity or situation in a particular light or context.
-
D.
fieldsPerFrame
Indicates the number of discrete fields that compose each video frame in an interlaced video signal.
-
E.
featuresSequence
Indicates that one entity presents or contains another entity as an ordered sequence of features or elements.
- F. None of above.
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_69f76eb0f86c819098dee07393e69ec3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.