Triple
T83018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seal of the President of the United States |
E1668
|
entity |
| Predicate | shieldStripesColor |
P60
|
FINISHED |
| Object | red and white |
—
|
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 and white | Statement: [Seal of the President of the United States, shieldStripesColor, red and white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shieldStripesColor Context triple: [Seal of the President of the United States, shieldStripesColor, red and white]
-
A.
numberOfStripes
Indicates the count of distinct stripe markings associated with an entity.
-
B.
ribbonAdditionalStripes
Indicates that additional stripes are present on a ribbon beyond its primary or standard design.
-
C.
camouflagePattern
Indicates that one entity has a surface or visual design intended to conceal it by blending with its surroundings or disrupting its outline.
-
D.
hatPattern
Indicates that one entity has a hat characterized by a specific pattern or design.
-
E.
colors
chosen
Indicates that one entity assigns, describes, or provides the color or colors of 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a25053ca208190a371b0d38000c2b9 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb2998c819082681da74601d446 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.