Triple
T16083521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Welwitschiaceae |
E390170
|
entity |
| Predicate | leafNumberCharacteristic |
P121830
|
FINISHED |
| Object | two persistent leaves |
—
|
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: two persistent leaves | Statement: [Welwitschiaceae, leafNumberCharacteristic, two persistent leaves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leafNumberCharacteristic Context triple: [Welwitschiaceae, leafNumberCharacteristic, two persistent leaves]
-
A.
typicalLeafCharacteristic
Indicates the usual or defining features of a leaf that characterize it under normal conditions.
-
B.
characteristicLeafIndumentum
Indicates the type or nature of surface covering (e.g., hairs, scales) that is characteristically present on a leaf.
-
C.
characteristicLeafTexture
Indicates the typical surface feel or texture that characterizes a leaf (e.g., smooth, rough, hairy) as a defining trait.
-
D.
leafArrangement
Indicates how leaves are positioned or organized on a plant’s stem or branches.
-
E.
leafVenationType
Indicates the pattern or arrangement of veins within a leaf.
- 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff63edb0819092cbb671967bbdcd |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e1827ad7c88190b867da511cbfb7fa |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e1ff5cd7e481908a29214139a3de2e |
completed | April 17, 2026, 9:37 a.m. |
Created at: April 10, 2026, 4:59 a.m.