Triple
T14048614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bicol Express |
E338024
|
entity |
| Predicate | commonlyEatenAt |
P104841
|
FINISHED |
| Object | lunch |
—
|
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: lunch | Statement: [Bicol Express, commonlyEatenAt, lunch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonlyEatenAt Context triple: [Bicol Express, commonlyEatenAt, lunch]
-
A.
typicallyEatenAt
Indicates that something is most commonly or customarily eaten during a particular time, event, or context.
-
B.
commonlyConsumedAt
chosen
Indicates that one entity is typically eaten or drunk during, or in association with, a particular time, event, or context.
-
C.
isEatenIn
Indicates that one entity (typically food) is consumed within the context, location, or occasion specified by another entity.
-
D.
isTypicallyServedFor
Indicates that one item is most commonly or customarily served as a meal or course for the other (e.g., a dish typically served for breakfast, lunch, or dinner).
-
E.
commonMealType
Indicates that two entities share the same general category or type of meal (e.g., breakfast, lunch, dinner).
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c88b5e48190b0f0149102c08992 |
completed | April 14, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:20 p.m.