Triple
T11537347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monica Helms |
E273583
|
entity |
| Predicate | hasPartInColorDesign |
P85337
|
FINISHED |
| Object | light blue stripes of the transgender pride flag |
—
|
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: light blue stripes of the transgender pride flag | Statement: [Monica Helms, hasPartInColorDesign, light blue stripes of the transgender pride flag]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartInColorDesign Context triple: [Monica Helms, hasPartInColorDesign, light blue stripes of the transgender pride flag]
-
A.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
B.
usesBrandColor
Indicates that one entity applies or displays another entity’s official brand color in its appearance, design, or materials.
-
C.
hasInteriorColor
Indicates that an entity possesses a specific color used on its interior surfaces or internal parts.
-
D.
containsColor
chosen
Indicates that one entity includes or exhibits the color specified by another entity.
-
E.
usesTricolorPattern
Indicates that an entity employs a three-color pattern as a defining or characteristic design element.
- 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_69d6aae3fbec8190a14632a5df2538b6 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8839cdf688190ae75c0e6fece8e33 |
completed | April 10, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_69d80879fdb48190be6dacc8aa63c809 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:37 p.m.