Triple
T25979642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | four-momentum operator |
E646031
|
entity |
| Predicate | frameTransformsAs |
P28224
|
FINISHED |
| Object | Lorentz four-vector |
—
|
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: Lorentz four-vector | Statement: [four-momentum operator, frameTransformsAs, Lorentz four-vector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frameTransformsAs Context triple: [four-momentum operator, frameTransformsAs, Lorentz four-vector]
-
A.
framesAs
Indicates how one entity presents, characterizes, or interprets another entity or situation in a particular light or context.
-
B.
transformsUnder
chosen
Indicates a relationship where one entity changes form, state, or structure when subjected to the influence, conditions, or operation specified by another entity.
-
C.
framesViewOf
Indicates that one entity provides a framing, perspective, or interpretive context through which another entity is viewed or understood.
-
D.
coordinateTransformation
Indicates a relationship where one coordinate system is mathematically converted or mapped into another, preserving the correspondence of points between them.
-
E.
regionTransformed
Indicates that one region has been changed or converted into another region through some transformation process.
- 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_69e77e881fc08190ba1c8dc7e2a07f97 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6050e507881909e3bc0c33e8a8c7e |
completed | May 2, 2026, 2:07 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fba5248190945acf1561280799 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 22, 2026, 8:54 a.m.