Triple
T9452353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna’s Taqueria |
E227922
|
entity |
| Predicate | hasDishStyle |
P14779
|
FINISHED |
| Object | Mission-style burrito |
—
|
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: Mission-style burrito | Statement: [Anna’s Taqueria, hasDishStyle, Mission-style burrito]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDishStyle Context triple: [Anna’s Taqueria, hasDishStyle, Mission-style burrito]
-
A.
hasDishType
Indicates that an item (such as a food or menu entry) is classified as belonging to a particular type of dish (e.g., appetizer, main course, dessert).
-
B.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
-
C.
diningStyle
Indicates the manner or format in which dining is conducted, such as casual, formal, buffet, or family-style.
-
D.
servingStyle
chosen
Indicates how something (typically food or drink) is presented or offered for consumption or use.
-
E.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
- 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_69ca8439f8bc8190997f2ef40c9f0bc2 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f68f9b081908bee041d4fc77e57 |
completed | April 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69cca5596ffc819097e9c8eefd4ef9b8 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:52 p.m.