Triple
T210674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kretschmann scalar |
E4709
|
entity |
| Predicate | isLocalQuantity |
P9159
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Kretschmann scalar, isLocalQuantity, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLocalQuantity Context triple: [Kretschmann scalar, isLocalQuantity, yes]
-
A.
quantifies
Indicates that one entity expresses or specifies the amount, number, or degree of another entity.
-
B.
hasLotSize
Indicates that an entity possesses a specific amount or extent of physical area, typically referring to the size of a parcel of land or property lot.
-
C.
usesMetric
Indicates that one entity adopts, applies, or relies on a particular metric or measurement standard in its operation, evaluation, or description.
-
D.
usesMeasurementSystem
Indicates that one entity adopts or applies a particular system of measurement defined by another entity.
-
E.
typicalUnitSize
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
- F. None of above. chosen
Provenance (4 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b4f71b88190866c8262922ae204 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25d3463648190ac716d7475378536 |
completed | Feb. 28, 2026, 3:12 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.