Triple
T27914439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teochew oyster omelette |
E706029
|
entity |
| Predicate | commonlyFoundIn |
P180371
|
FINISHED |
| Object | Teochew restaurants |
—
|
NE NERFINISHED |
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: Teochew restaurants | Statement: [Teochew oyster omelette, commonlyFoundIn, Teochew restaurants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonlyFoundIn Context triple: [Teochew oyster omelette, commonlyFoundIn, Teochew restaurants]
-
A.
commonlyFoundOn
Indicates that one entity is typically or frequently located on, attached to, or present upon another entity.
-
B.
isCommonlyFoundAt
chosen
Indicates that an entity typically or frequently occurs, appears, or is present in a particular location or context.
-
C.
traditionallyFoundIn
Indicates that something is customarily or historically located, used, or present within a particular place, context, or setting.
-
D.
foundInFood
Indicates that a substance, ingredient, or component is present within or contained in a particular food item.
-
E.
isAlsoFoundIn
Indicates that the same entity or item occurs or exists in another specified location, context, or collection as well.
- 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_69ef96b6cc808190aab19fb18b235f4b |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f7a225a77c81908f8953ccfeb14336 |
completed | May 3, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69f7a06d4f108190bae3ab9ae431d2c7 |
completed | May 3, 2026, 7:22 p.m. |
Created at: April 27, 2026, 6:52 p.m.