Triple
T15409270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Checkers franchises |
E368541
|
entity |
| Predicate | typicalMenuItem |
P101738
|
FINISHED |
| Object | burgers |
—
|
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: burgers | Statement: [Checkers franchises, typicalMenuItem, burgers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMenuItem Context triple: [Checkers franchises, typicalMenuItem, burgers]
-
A.
typicalItem
chosen
Indicates that an item is a representative or characteristic example of a broader category, class, or set.
-
B.
menuItemType
Indicates the relationship between a menu item and the type or category it belongs to (e.g., appetizer, main course, dessert).
-
C.
foodItem
Indicates that one entity is a food item that can be eaten or used as food in relation to another entity.
-
D.
typicalOrder
Indicates the usual or most common sequence or arrangement in which related elements, events, or components occur.
-
E.
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).
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ea4f13c819085d26fd32b5dca6f |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded27b8cac8190bfa77698d53c5d1c |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:20 a.m.