Triple
T29673693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney Casual Table-Service Dining category |
E750742
|
entity |
| Predicate | hasMenuRange |
P194013
|
FINISHED |
| Object | American cuisine |
—
|
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: American cuisine | Statement: [Disney Casual Table-Service Dining category, hasMenuRange, American cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMenuRange Context triple: [Disney Casual Table-Service Dining category, hasMenuRange, American cuisine]
-
A.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
-
B.
hasRangeCategory
Indicates that a property or measurement falls within a specified category or interval of possible values.
-
C.
hasMenuItem
Indicates that one entity (typically a menu or menu section) includes or offers another entity as one of its menu items.
-
D.
hasMenuBoard
Indicates that one entity provides or is equipped with a menu board associated with another entity.
-
E.
tieneRango
Indicates that one entity possesses, is assigned, or falls within a specific rank or range in relation to another entity.
- F. None of above. chosen
Provenance (4 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_69f0d624d7b08190ba237d226f78d0d9 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fd5d48855c8190bd93070b6a00d8b5 |
completed | May 8, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69fd5c9aabb88190912800d90184a89d |
completed | May 8, 2026, 3:46 a.m. |
| PDg | Predicate description generation | batch_69fd5d47da488190a4f2dbd44a0a83b2 |
completed | May 8, 2026, 3:49 a.m. |
Created at: April 28, 2026, 7:06 p.m.