Triple
T34172097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayflower pub |
E876570
|
entity |
| Predicate | hasDrinkingEstablishmentType |
P178478
|
FINISHED |
| Object | riverside pub |
—
|
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 pub | Statement: [Mayflower pub, hasDrinkingEstablishmentType, riverside pub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDrinkingEstablishmentType Context triple: [Mayflower pub, hasDrinkingEstablishmentType, riverside pub]
-
A.
hasAlcoholLicense
Indicates that an entity possesses a valid authorization or permit to sell, serve, or distribute alcoholic beverages.
-
B.
servesAlcohol
Indicates that an establishment or provider offers and supplies alcoholic beverages to customers or participants.
-
C.
hasRestaurantType
Indicates that an entity is associated with or classified as a particular type or category of restaurant.
-
D.
hasBreweryOrFacility
Indicates that an entity possesses, operates, or is associated with a brewery or brewing-related facility.
-
E.
hasRestaurantsAndBars
Indicates that the subject location contains or provides access to both restaurants and bars.
- 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_69f349ad97ac8190bf1f17417c970e64 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f710aaff588190adc6cc5b7d5424cc |
completed | May 3, 2026, 9:08 a.m. |
| PD | Predicate disambiguation | batch_69f70f3c5bfc81908585f52e196dafe5 |
completed | May 3, 2026, 9:02 a.m. |
| PDg | Predicate description generation | batch_69f70fddd43c819088dee5a448c72cbe |
completed | May 3, 2026, 9:05 a.m. |
Created at: May 1, 2026, 1:54 a.m.