Triple
T12727518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moqueca baiana |
E304143
|
entity |
| Predicate | typicalSpiceOrHerb |
P102161
|
FINISHED |
| Object | cilantro |
—
|
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: cilantro | Statement: [Moqueca baiana, typicalSpiceOrHerb, cilantro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSpiceOrHerb Context triple: [Moqueca baiana, typicalSpiceOrHerb, cilantro]
-
A.
typicalSpices
chosen
Indicates that certain spices are commonly or characteristically used in association with a particular dish, cuisine, or ingredient.
-
B.
includesHerb
Indicates that one entity contains or incorporates a herb as part of its composition or contents.
-
C.
ingredientType
Indicates that one entity is classified as a specific type or category of ingredient in relation to another.
-
D.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
E.
hasSpice
Indicates that one entity contains, includes, or is characterized by a particular spice or set of spices.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96403957c81909acdee7bdae71696 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:25 p.m.