Triple
T16516290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burroughs Medal |
E401192
|
entity |
| Predicate | isNonFictionAward |
P24758
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Burroughs Medal, isNonFictionAward, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNonFictionAward Context triple: [Burroughs Medal, isNonFictionAward, true]
-
A.
isNonFictionCategory
Indicates that a given category pertains to non-fiction works, such as factual or informational content rather than fictional material.
-
B.
isNonProfitAward
Indicates that an award is specifically designated for or granted to nonprofit organizations or initiatives.
-
C.
awardWithinFiction
Indicates that an award is given or exists within a fictional context or narrative world, rather than in real life.
-
D.
isNonProfessionalAward
Indicates that an award is given in a non-professional context, typically recognizing amateur, volunteer, or informal achievements rather than professional accomplishments.
-
E.
isNonfiction
chosen
Indicates that the work or content is factual rather than fictional, based on real events, people, or information.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e7c7e588190acbcc2b807a98909 |
completed | April 18, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69e296995d388190b88ebe189dce890d |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:14 a.m.