Triple
T14991209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | g-2 |
E373838
|
entity |
| Predicate | hasQuantityType |
P20230
|
FINISHED |
| Object | dimensionless |
—
|
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: dimensionless | Statement: [g-2, hasQuantityType, dimensionless]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasQuantityType Context triple: [g-2, hasQuantityType, dimensionless]
-
A.
hasBaseQuantity
Indicates that something is associated with or defined in terms of a fundamental underlying quantity.
-
B.
quantificationType
chosen
Indicates the specific kind or category of quantity or measurement being applied in a given context.
-
C.
hasKeyQuantity
Indicates that an entity is associated with a primary or defining quantity that characterizes or measures it.
-
D.
usesQuantity
Indicates that one entity employs or applies a specified amount or measure of another entity in performing an action or fulfilling a function.
-
E.
belongsToQuantityKind
Indicates that something is associated with, or classified under, a particular kind or category of quantity (such as length, mass, or time).
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded715db408190b44e8a8452c79764 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:53 a.m.