Triple
T7859042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woman with Plants |
E182446
|
entity |
| Predicate | depictsPlantType |
P4282
|
FINISHED |
| Object | houseplants |
—
|
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: houseplants | Statement: [Woman with Plants, depictsPlantType, houseplants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsPlantType Context triple: [Woman with Plants, depictsPlantType, houseplants]
-
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.
involvesPlant
Indicates that the relationship or action includes or pertains to a plant as a participating entity.
-
D.
hasPlantSymbol
Indicates that an entity is associated with or represented by a particular plant as its symbolic emblem or sign.
-
E.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
- 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_69ca82887fd48190975896bf38c4596b |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb1a787c8c8190bcd9ed76cc7aa4c5 |
completed | March 31, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69cae925ca388190ae4a01fa76e957e8 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:53 p.m.