Triple
T3734908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magnolia |
E79157
|
entity |
| Predicate | hasFlowerCharacteristic |
P12303
|
FINISHED |
| Object | large blossoms |
—
|
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: large blossoms | Statement: [Magnolia, hasFlowerCharacteristic, large blossoms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlowerCharacteristic Context triple: [Magnolia, hasFlowerCharacteristic, large blossoms]
-
A.
hasFlowerColor
Indicates that an entity (typically a plant or flower) possesses a specific flower color.
-
B.
flowerType
Indicates the specific kind or category of flower associated with an entity.
-
C.
flowerCharacteristic
chosen
Indicates that a flower possesses a particular attribute, quality, or feature (such as color, shape, size, or scent).
-
D.
hasSpecializedPetal
Indicates that an entity possesses petals that are specialized or modified for a particular function or role.
-
E.
floweringUse
Indicates the use or application of something specifically for flowering or promoting the flowering process.
- 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_69ad8b0e4650819090ad7cef094285e8 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb39dc0881909cd74ff25d8c43a9 |
completed | March 8, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69adc04746588190b0dc535638f23546 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.