Triple
T28144039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungry Bear Restaurant |
E714425
|
entity |
| Predicate | hasDiningLocationType |
P55802
|
FINISHED |
| Object | riverside eatery |
—
|
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: riverside eatery | Statement: [Hungry Bear Restaurant, hasDiningLocationType, riverside eatery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiningLocationType Context triple: [Hungry Bear Restaurant, hasDiningLocationType, riverside eatery]
-
A.
hasDiningOptionType
Indicates that an entity offers or is associated with a specific type or category of dining option (e.g., dine-in, takeout, delivery).
-
B.
isDiningDestination
Indicates that a place serves as a destination where people go specifically to eat meals or dine.
-
C.
hasDiningComponent
Indicates that something includes or is associated with a dining-related part, feature, or function.
-
D.
hasDiningFeature
chosen
Indicates that something possesses a specific characteristic, amenity, or attribute related to dining.
-
E.
hasDiningFocus
Indicates that an entity is primarily oriented toward or specialized in dining-related activities, services, or experiences.
- 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_69efd6b033208190bf74f80a147e2092 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: April 27, 2026, 9:55 p.m.