Triple
T1285971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newton's second law of motion |
E27433
|
entity |
| Predicate | hasVectorForm |
P2894
|
FINISHED |
| Object | ΣF⃗ = m a⃗ |
—
|
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: ΣF⃗ = m a⃗ | Statement: [Newton's second law of motion, hasVectorForm, ΣF⃗ = m a⃗]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVectorForm Context triple: [Newton's second law of motion, hasVectorForm, ΣF⃗ = m a⃗]
-
A.
hasVector
chosen
Indicates that an entity is associated with, or can be represented by, a specific vector in some vector space.
-
B.
vector
Indicates that one entity is a vector associated with, representing, or characterizing another entity (such as a quantity with magnitude and direction, or a carrier/representative of something).
-
C.
hasForm
Indicates that one entity possesses, exhibits, or is characterized by a particular shape, structure, or configuration.
-
D.
hasNonStandardForm
Indicates that an entity possesses a form, variant, or representation that deviates from the standard, canonical, or commonly accepted form.
-
E.
hasFullForm
Indicates that one entity is the complete, expanded, or unabbreviated form of another entity.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0b85eb48190a8b61dc397fa6390 |
completed | March 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69a4bee276d8819092f71c5a1140bb61 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.