Triple
T14908858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mediterranean forests, woodlands and scrub |
E371206
|
entity |
| Predicate | typicalPlantTrait |
P100875
|
FINISHED |
| Object | small hard 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: small hard leaves | Statement: [Mediterranean forests, woodlands and scrub, typicalPlantTrait, small hard leaves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPlantTrait Context triple: [Mediterranean forests, woodlands and scrub, typicalPlantTrait, small hard leaves]
-
A.
typicalLeafCharacteristic
Indicates the usual or defining features of a leaf that characterize it under normal conditions.
-
B.
agronomicTrait
Indicates a relationship where a trait is characterized specifically in terms of its relevance to agricultural growth, management, or productivity of plants or crops.
-
C.
treeHabit
Indicates the growth form or structural habit characteristic of a tree, such as its typical shape, branching pattern, or overall stature.
-
D.
hasGrowthHabit
Indicates the characteristic way in which an organism typically grows or develops in form or structure.
-
E.
lifeCharacteristic
chosen
Indicates that an entity possesses a particular trait, feature, or quality relevant to its life or living state.
- 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded61b3c808190b4f6df4e5cb401ad |
completed | April 15, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69de9a4a14a88190951bb8f4c60bd37b |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:25 a.m.