Triple
T3487917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poynting vector |
E73653
|
entity |
| Predicate | hasPhysicalDimensionSymbol |
P26854
|
FINISHED |
| Object | M¹T⁻³ |
—
|
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: M¹T⁻³ | Statement: [Poynting vector, hasPhysicalDimensionSymbol, M¹T⁻³]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhysicalDimensionSymbol Context triple: [Poynting vector, hasPhysicalDimensionSymbol, M¹T⁻³]
-
A.
dimensionSymbol
chosen
Indicates a symbolic notation that represents or labels a specific dimension or measurement attribute in a context.
-
B.
SIUnitSymbol
Indicates the standardized symbol used to represent a quantity in the International System of Units (SI).
-
C.
hasDimensionlessParameter
Indicates that an entity is associated with a parameter that has no physical units (a pure, dimensionless quantity).
-
D.
hasDimension
Indicates that an entity possesses a specific measurable extent or size along one or more axes (e.g., length, width, height).
-
E.
hasNationalDimension
Indicates that something possesses a scope, relevance, or impact at the level of a nation or entire country.
- 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_69ad85cca8d4819088494e9f3340fab5 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbb9193688190aa0cbf87a7b99446 |
completed | March 8, 2026, 6:10 p.m. |
| PD | Predicate disambiguation | batch_69adae0935ac8190bfa8a8bd3dcd3301 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:18 p.m.