Triple
T17348564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinapis alba |
E421747
|
entity |
| Predicate | pungencySource |
P127130
|
FINISHED |
| Object | enzymatic breakdown of glucosinolates |
—
|
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: enzymatic breakdown of glucosinolates | Statement: [Sinapis alba, pungencySource, enzymatic breakdown of glucosinolates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pungencySource Context triple: [Sinapis alba, pungencySource, enzymatic breakdown of glucosinolates]
-
A.
hasSpiciness
Indicates that one entity possesses a certain level or quality of spiciness in relation to another entity or a defined scale.
-
B.
hasTasteIntensity
Indicates the degree or strength of taste associated with something.
-
C.
crunchiness
Indicates the degree to which something produces a firm, crisp sound and texture when bitten or broken.
-
D.
bitterantType
Indicates the specific kind or category of bitterant used or associated with an entity.
-
E.
tongueTincture
Indicates that an entity applies or administers a tincture by placing it on or under the tongue.
- F. None of above. chosen
Provenance (4 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a2af5f88190b4c292ca30993b36 |
completed | April 19, 2026, 2:12 a.m. |
| PD | Predicate disambiguation | batch_69e3b02662d08190a07d0fb5c04b6f33 |
completed | April 18, 2026, 4:24 p.m. |
| PDg | Predicate description generation | batch_69e3b2a225b08190a50f984caa6513b9 |
completed | April 18, 2026, 4:34 p.m. |
Created at: April 10, 2026, 5:44 a.m.