Triple
T2591442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lavender Mist (Number 1, 1950) |
E58129
|
entity |
| Predicate | dimensionUnit |
P12631
|
FINISHED |
| Object | centimetre |
—
|
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: centimetre | Statement: [Lavender Mist (Number 1, 1950), dimensionUnit, centimetre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimensionUnit Context triple: [Lavender Mist (Number 1, 1950), dimensionUnit, centimetre]
-
A.
dimensionSymbol
Indicates a symbolic notation that represents or labels a specific dimension or measurement attribute in a context.
-
B.
typeOfUnit
Indicates that one entity specifies the kind or category of measurement unit that the other entity belongs to.
-
C.
dimensionType
Indicates the specific kind or category of dimension that characterizes how something is measured or structured.
-
D.
unitOfMeasure
chosen
Indicates that one entity specifies the standard unit in which the quantity or value of another entity is measured.
-
E.
unitSystem
Indicates the system of measurement units (such as metric or imperial) that is used to quantify associated values or attributes.
- 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_69ab4ac019c8819094add11c46706e32 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd425851c819088db89713c07056f |
completed | March 7, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69abd0d19308819089ee942513d567a4 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.