Triple
T23193144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melicope |
E579801
|
entity |
| Predicate | leafTrait |
P17481
|
FINISHED |
| Object | gland-dotted 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: gland-dotted leaves | Statement: [Melicope, leafTrait, gland-dotted leaves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leafTrait Context triple: [Melicope, leafTrait, gland-dotted leaves]
-
A.
leafType
Indicates the specific kind or classification of leaf associated with an entity.
-
B.
typicalLeafCharacteristic
chosen
Indicates the usual or defining features of a leaf that characterize it under normal conditions.
-
C.
leafProperty
Indicates that the subject has a property that is terminal (i.e., not further decomposed into sub-properties) within a property hierarchy or structure.
-
D.
foliageCharacteristic
Indicates the specific traits or qualities of an entity’s foliage, such as its type, texture, color, or other distinguishing features.
-
E.
characteristicLeafIndumentum
Indicates the type or nature of surface covering (e.g., hairs, scales) that is characteristically present on a leaf.
- 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_69e24600eed08190bd7e5295653a1503 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18fd971d08190a132d24094e0c37b |
completed | April 29, 2026, 4:58 a.m. |
| PD | Predicate disambiguation | batch_69ef8a041c0081909afb670d17a5aaba |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4:06 p.m.