Triple
T15845391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clonakilty |
E384199
|
entity |
| Predicate | hasAwardWinningFood |
P17971
|
FINISHED |
| Object | black pudding |
—
|
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: black pudding | Statement: [Clonakilty, hasAwardWinningFood, black pudding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAwardWinningFood Context triple: [Clonakilty, hasAwardWinningFood, black pudding]
-
A.
hasSpecialtyFood
chosen
Indicates that an entity offers, serves, or is associated with a particular type of specialty food.
-
B.
hasStapleFood
Indicates that an entity’s primary or regularly consumed basic food item is another specified entity.
-
C.
hasMichelinStar
Indicates that a restaurant or dining establishment has been awarded at least one Michelin star for its culinary quality.
-
D.
isPrizedFor
Indicates that something is highly valued or esteemed because of a particular quality, feature, or benefit it provides.
-
E.
haveCuisine
Indicates that an entity (such as a restaurant or place) offers, serves, or is associated with a particular type or style of cuisine.
- 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e14ca636048190bc89cd8b4efa89e9 |
completed | April 16, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69e005434ed88190baf11c169da3cf29 |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:50 a.m.