Triple
T13396462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syzygium |
E319712
|
entity |
| Predicate | includesPlantsWithUse |
P51056
|
FINISHED |
| Object | culinary spice |
—
|
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: culinary spice | Statement: [Syzygium, includesPlantsWithUse, culinary spice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesPlantsWithUse Context triple: [Syzygium, includesPlantsWithUse, culinary spice]
-
A.
containsPlantsWith
Indicates that one entity includes or holds within it one or more plant entities.
-
B.
plantUse
chosen
Indicates that a plant is used for a particular purpose, function, or application.
-
C.
involvesPlant
Indicates that the relationship or action includes or pertains to a plant as a participating entity.
-
D.
includesOrnamentalPlant
Indicates that one entity contains, features, or has as part of it an ornamental plant used primarily for decorative purposes.
-
E.
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).
- 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.