Triple
T1043502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Note |
E22521
|
entity |
| Predicate | colorOfSeal |
P23866
|
FINISHED |
| Object | red Treasury seal on small-size notes |
—
|
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: red Treasury seal on small-size notes | Statement: [United States Note, colorOfSeal, red Treasury seal on small-size notes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorOfSeal Context triple: [United States Note, colorOfSeal, red Treasury seal on small-size notes]
-
A.
seal
Indicates that an agent closes or fastens something so that it is securely shut and often airtight or watertight.
-
B.
firstSealAssociatedWith
Indicates that an entity is the earliest or primary seal linked or connected to another entity.
-
C.
coneColor
Indicates that one entity is the color attribute assigned to a cone-shaped object.
-
D.
spurColor
Indicates the color of the spur associated with an entity.
-
E.
ribbonColours
Indicates that there is an association between an entity and one or more colours of ribbons related to it.
- 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8475ab48190848388eea6448cb6 |
completed | March 1, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69a4b72ba60881908b017ef3b2b9645e |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b8444f708190815732408aa0463e |
completed | March 1, 2026, 10:05 p.m. |
Created at: March 1, 2026, 7:42 p.m.