Triple
T11537350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monica Helms |
E273583
|
entity |
| Predicate | flagDesignSymbolism |
P99574
|
FINISHED |
| Object | light blue represents traditional color for baby boys |
—
|
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 represents traditional color for baby boys | Statement: [Monica Helms, flagDesignSymbolism, light blue represents traditional color for baby boys]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flagDesignSymbolism Context triple: [Monica Helms, flagDesignSymbolism, light blue represents traditional color for baby boys]
-
A.
emblemSymbolism
Indicates that one entity serves as an emblem whose design or features symbolically represent or convey meanings about another entity.
-
B.
flagOrInsignia
Indicates that one entity serves as a flag, emblem, or insignia representing another entity.
-
C.
religiousSymbolOnFlag
Indicates that a flag features a symbol associated with a religion as part of its design.
-
D.
shapeSymbolism
Indicates how a particular shape is associated with or conveys symbolic meaning within a given context.
-
E.
flagDesigner
Indicates that one entity is the person or group responsible for designing the flag associated with another entity.
- 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_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. |
| PDg | Predicate description generation | batch_69d8279925e4819089210611c0d8e61a |
completed | April 9, 2026, 10:26 p.m. |
Created at: April 8, 2026, 9:37 p.m.