Triple
T244302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorentz transformation |
E5001
|
entity |
| Predicate | generalizedIn |
P6829
|
FINISHED |
| Object | general relativity via local Lorentz invariance |
—
|
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: general relativity via local Lorentz invariance | Statement: [Lorentz transformation, generalizedIn, general relativity via local Lorentz invariance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: generalizedIn Context triple: [Lorentz transformation, generalizedIn, general relativity via local Lorentz invariance]
-
A.
generalizationOf
Indicates that one entity represents a broader, more general concept or category that subsumes or abstracts over another, more specific entity.
-
B.
commonIn
Indicates that something frequently occurs, appears, or is found within a specified context, group, or environment.
-
C.
includes
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
D.
standardizedIn
Indicates that something has been formally defined, regulated, or made uniform within a particular standard, framework, or jurisdiction.
-
E.
alsoUsedIn
chosen
Indicates that something is additionally employed, applied, or present in another context, setting, or use case beyond the primary one.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b62839c8190824064fe5da6a92a |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.