Triple
T36380522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gomortegaceae |
E896031
|
entity |
| Predicate | leafTypeOfBestKnownSpecies |
P572
|
FINISHED |
| Object | evergreen 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: evergreen leaves | Statement: [Gomortegaceae, leafTypeOfBestKnownSpecies, evergreen leaves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leafTypeOfBestKnownSpecies Context triple: [Gomortegaceae, leafTypeOfBestKnownSpecies, evergreen leaves]
-
A.
leafType
chosen
Indicates the specific kind or classification of leaf associated with an entity.
-
B.
typicalLeafCharacteristic
Indicates the usual or defining features of a leaf that characterize it under normal conditions.
-
C.
taxonType
Indicates the biological or taxonomic rank/category that characterizes a given taxon.
-
D.
leafNumberCharacteristic
Indicates a relationship where an entity is associated with a specific count or quantitative characteristic of its leaves.
-
E.
treeHabit
Indicates the growth form or structural habit characteristic of a tree, such as its typical shape, branching pattern, or overall stature.
- 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_69f76e51d358819092bbc5f119f49476 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb3ff1b08190802b1063d55d3923 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a611a081908dd6aec1df3f4d7f |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:10 p.m.