Triple
T993441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giller Prize |
E21442
|
entity |
| Predicate | workScope |
P22281
|
FINISHED |
| Object | single book of fiction |
—
|
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: single book of fiction | Statement: [Giller Prize, workScope, single book of fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workScope Context triple: [Giller Prize, workScope, single book of fiction]
-
A.
workBy
Indicates that a work (such as a creation, product, or result) is produced, authored, or created by a particular agent or entity.
-
B.
officeScope
Indicates that a relationship, authority, or action is limited to, defined within, or applicable only in the context of a particular office or official position.
-
C.
workIncludes
Indicates that a work (such as a project, document, or creative piece) contains or incorporates another specified component, part, or element.
-
D.
workRelatedTo
Indicates a relationship where one entity’s work, tasks, or professional activities are connected, associated, or relevant to those of another entity.
-
E.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4c5e16881908cd5f7ba2fcd5084 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2adbde48190b07966d0c3179516 |
completed | March 1, 2026, 9:42 p.m. |
| PDg | Predicate description generation | batch_69a4b38723d8819098b861cba5cad4ee |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:41 p.m.