Triple
T13396072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melastomataceae |
E319703
|
entity |
| Predicate | typeOfPlant |
P4282
|
FINISHED |
| Object | dicotyledon |
—
|
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: dicotyledon | Statement: [Melastomataceae, typeOfPlant, dicotyledon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfPlant Context triple: [Melastomataceae, typeOfPlant, dicotyledon]
-
A.
plantType
chosen
Indicates the specific kind or category of plant that an entity is classified as.
-
B.
isPlantOf
Indicates that one entity is a plant that belongs to, is associated with, or is characteristic of another entity (such as a region, habitat, or owner).
-
C.
isHouseplant
Indicates that an entity is a plant typically grown and kept indoors as a houseplant.
-
D.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
E.
plant
Indicates that an entity places or sets something firmly in or on a location, often so it will grow, remain fixed, or be established there.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dba0d892d08190b1b192b93fe3d72d |
completed | April 12, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03189908190a784a2755f8d81e1 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:34 p.m.