Triple
T479083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aji de gallina |
E9125
|
entity |
| Predicate | typicalSpiciness |
P12843
|
FINISHED |
| Object | mildly spicy |
—
|
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: mildly spicy | Statement: [Aji de gallina, typicalSpiciness, mildly spicy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSpiciness Context triple: [Aji de gallina, typicalSpiciness, mildly spicy]
-
A.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
B.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
C.
typicalVariety
Indicates that one entity is a representative or characteristic example of the variety or type defined by another entity.
-
D.
acidityLevel
Indicates the degree or intensity of acidity associated with an entity, typically measured by pH or a comparable scale.
-
E.
typicalDegree
chosen
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f056459881909749764cc4a7f9e8 |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edf1d5848190a7da27e2fddc136f |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.