Triple
T1741286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columbus Day Parade |
E38237
|
entity |
| Predicate | hasVisualSymbol |
P10282
|
FINISHED |
| Object | Italian tricolor |
—
|
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: Italian tricolor | Statement: [Columbus Day Parade, hasVisualSymbol, Italian tricolor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVisualSymbol Context triple: [Columbus Day Parade, hasVisualSymbol, Italian tricolor]
-
A.
hasColorSymbol
Indicates that one entity is associated with another entity that serves as its representative or symbolic color.
-
B.
appearsWithSymbol
Indicates that one entity is shown or presented together with a particular symbol in the same visual or contextual setting.
-
C.
hasTraditionalSymbol
chosen
Indicates that something is associated with or represented by a conventional or culturally established symbol.
-
D.
visionOrSign
Indicates a relationship where something is perceived or presented as a vision, sign, or symbolic manifestation, often conveying a message, omen, or divine indication.
-
E.
visualElements
Indicates that one entity contains, uses, or is characterized by specific visual components or graphical features associated with another entity.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab3c2559ac8190905186406fcaccb9 |
completed | March 6, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69aa61c4023c819099cbe439aefda71f |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.