Triple
T20873293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rafflesiaceae |
E513947
|
entity |
| Predicate | flowerSizeCharacteristic |
P12303
|
FINISHED |
| Object | among the largest flowers in the world |
—
|
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: among the largest flowers in the world | Statement: [Rafflesiaceae, flowerSizeCharacteristic, among the largest flowers in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flowerSizeCharacteristic Context triple: [Rafflesiaceae, flowerSizeCharacteristic, among the largest flowers in the world]
-
A.
flowerCharacteristic
chosen
Indicates that a flower possesses a particular attribute, quality, or feature (such as color, shape, size, or scent).
-
B.
flowerHeadDiameter
Indicates the diameter measurement across the head of a flower.
-
C.
flowerType
Indicates the specific kind or category of flower associated with an entity.
-
D.
hasFloralFeature
Indicates that an entity possesses a specific floral characteristic, structure, or attribute.
-
E.
flowerSymmetry
Indicates the type or pattern of symmetry exhibited by a flower’s structure or arrangement of its parts.
- 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_69e0b4f675cc8190b4e745225b62eb66 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c46639308190a616193f3975d453 |
completed | April 21, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a8dc148190b33ff51894e2a8f9 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:45 p.m.