Triple
T31220806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | capsaicin |
E796003
|
entity |
| Predicate | hasScovilleHeatUnitValue |
P185652
|
FINISHED |
| Object | 16,000,000 SHU (pure capsaicin) |
—
|
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: 16,000,000 SHU (pure capsaicin) | Statement: [capsaicin, hasScovilleHeatUnitValue, 16,000,000 SHU (pure capsaicin)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScovilleHeatUnitValue Context triple: [capsaicin, hasScovilleHeatUnitValue, 16,000,000 SHU (pure capsaicin)]
-
A.
hasSpiciness
Indicates that one entity possesses a certain level or quality of spiciness in relation to another entity or a defined scale.
-
B.
isSpicy
Indicates that something has a hot or pungent flavor, typically due to the presence of strong seasonings or chili.
-
C.
hasSpice
Indicates that one entity contains, includes, or is characterized by a particular spice or set of spices.
-
D.
hasBitternessLevel
Indicates that an entity is associated with a specific degree or intensity of bitterness.
-
E.
spicinessAdjustable
Indicates that the level of spiciness associated with an item can be modified or customized.
- 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_69f224d9d52c8190a61f68ded37fa755 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7c33d59808190b647989a093f3488 |
completed | May 3, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
| PDg | Predicate description generation | batch_69f7c29cf36481908e472d4dcb5573b9 |
completed | May 3, 2026, 9:48 p.m. |
Created at: April 29, 2026, 9:10 p.m.