Triple
T5182450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Governor General's Award for English-language poetry |
E116951
|
entity |
| Predicate | awardedForWorksPublishedIn |
P15639
|
FINISHED |
| Object | previous year |
—
|
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: previous year | Statement: [Governor General's Award for English-language poetry, awardedForWorksPublishedIn, previous year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardedForWorksPublishedIn Context triple: [Governor General's Award for English-language poetry, awardedForWorksPublishedIn, previous year]
-
A.
authorAwardedForBodyOfWork
Indicates that an author received an award recognizing their entire body of work rather than a single specific piece.
-
B.
awardReceivedByWork
chosen
Indicates that a particular award was given in recognition of a specific work (such as a book, film, or artwork).
-
C.
notableAwardWork
Indicates that a work is the specific creation (e.g., book, film, artwork) for which an award or honor was given.
-
D.
hasAwardedFieldOfWork
Indicates that an entity has received an award specifically for work or contributions in a particular field or area of activity.
-
E.
awardedAuthor
Indicates that an author has received an award or recognition.
- 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_69bd446140f08190becb93c61158f27f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd799d50388190bf2b7dfdd90949e9 |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b7e8b4819092ec3965e11f2dea |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:46 p.m.