Triple
T21580940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of Bavaria |
E532519
|
entity |
| Predicate | lozengesPattern |
P144340
|
FINISHED |
| Object | bendy lozengy |
—
|
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: bendy lozengy | Statement: [Coat of arms of Bavaria, lozengesPattern, bendy lozengy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lozengesPattern Context triple: [Coat of arms of Bavaria, lozengesPattern, bendy lozengy]
-
A.
patroonOf
Indicates a relationship in which one entity acts as a patron, sponsor, or protector providing support or resources to another entity.
-
B.
wingPattern
Indicates the characteristic arrangement or design present on an entity's wings.
-
C.
maskPattern
Indicates a relationship where one entity serves as a masking template or pattern that determines which parts or aspects of another entity are revealed, hidden, or transformed.
-
D.
airingPattern
Indicates the recurring schedule or pattern according to which something (such as a program or content) is broadcast or made available.
-
E.
glazingPattern
Indicates the arrangement or design pattern of glazing elements (such as panes or glass sections) within a structure or object.
- 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_69e0c4618bec8190bcb0feb74568cbb1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eeeb5c496c819093113dd5790fca48 |
completed | April 27, 2026, 4:51 a.m. |
| PD | Predicate disambiguation | batch_69e6320c8c2c81908bf031447d66a052 |
completed | April 20, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69e633bf34c481909925d8dc1a633a65 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 16, 2026, 6:31 p.m.