Triple
T4682681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Canada |
E103840
|
entity |
| Predicate | redPanelWidthFraction |
P49883
|
FINISHED |
| Object | 1/4 of flag length each |
—
|
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: 1/4 of flag length each | Statement: [Flag of Canada, redPanelWidthFraction, 1/4 of flag length each]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: redPanelWidthFraction Context triple: [Flag of Canada, redPanelWidthFraction, 1/4 of flag length each]
-
A.
redStripeProportion
chosen
Indicates the proportion of an object’s area or length that is occupied by a red stripe.
-
B.
typicalPanelSize
Indicates the usual or standard dimensions associated with a given panel.
-
C.
maximumPanelSize
Indicates the largest allowable or supported size for a given panel in the specified context.
-
D.
blueStripeProportion
Indicates the proportion of an entity’s surface or area that is covered by a blue stripe relative to its total extent.
-
E.
yellowStripeProportion
Indicates the proportion of an object’s surface or area that is covered by yellow stripes.
- 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_69bd43debbf08190b4bc372e286ec234 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6217e0088190836570522e324dc6 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:16 p.m.