Triple
T5906003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mapo tofu |
E131341
|
entity |
| Predicate | hasVegetarianVariant |
P34157
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Mapo tofu, hasVegetarianVariant, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVegetarianVariant Context triple: [Mapo tofu, hasVegetarianVariant, yes]
-
A.
isVegetarian
Indicates that an entity follows a vegetarian diet, avoiding the consumption of meat and possibly other animal products.
-
B.
isNonVegetarian
Indicates that an entity consumes or includes meat or animal-based products, and therefore does not follow a vegetarian diet.
-
C.
dietaryOptions
chosen
Indicates the types of diets or food-related preferences, restrictions, or choices that are applicable to or offered for an entity.
-
D.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
E.
hasMainIngredient
Indicates that one entity is the primary or most significant ingredient used to make 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_69c0085864a88190a569c05ff7d65f29 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0334fcf6481908e8e74105de9d49b |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:59 p.m.