Triple
T5906018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mapo tofu |
E131341
|
entity |
| Predicate | goesWellWith |
P14740
|
FINISHED |
| Object | plain rice |
—
|
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: plain rice | Statement: [Mapo tofu, goesWellWith, plain rice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goesWellWith Context triple: [Mapo tofu, goesWellWith, plain rice]
-
A.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
B.
typicalFoodPairing
chosen
Indicates that one food item is commonly served, consumed, or matched together with another as a customary or complementary pairing.
-
C.
complements
Indicates that one entity enhances, completes, or improves another by providing qualities or functions that fit well together.
-
D.
usesIngredient
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
E.
ingredientType
Indicates that one entity is classified as a specific type or category of ingredient in relation to another.
- 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.