Triple
T9407590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Montserrat |
E226625
|
entity |
| Predicate | usesProportion |
P16308
|
FINISHED |
| Object | 1:2 |
—
|
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: 1:2 | Statement: [Flag of Montserrat, usesProportion, 1:2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesProportion Context triple: [Flag of Montserrat, usesProportion, 1:2]
-
A.
hasProportion
chosen
Indicates that one entity stands in a specified ratio, fraction, or relative share to another entity or whole.
-
B.
isProportionalTo
Indicates that one quantity varies in constant ratio to another, so when one changes, the other changes by a fixed multiplicative factor.
-
C.
hasProportionSystem
Indicates that one entity possesses or is characterized by a particular system for managing or defining proportions or ratios.
-
D.
isProportionalityFactorIn
Indicates that one quantity serves as the proportionality factor (constant of proportionality) in a specified proportional relationship or equation.
-
E.
usesProp
Indicates that one entity employs, utilizes, or makes use of a particular property, resource, or object in performing an action or fulfilling a function.
- 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_69ca843280488190bc65600e843ef9e6 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5252b3fc8190b0808a10987728c8 |
completed | April 1, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69cca54c37f88190bddccf28e5fe5c84 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:47 p.m.