Triple
T29017587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Worlds of If |
E737357
|
entity |
| Predicate | HugoAwardBestProzineWins |
P165916
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Worlds of If, HugoAwardBestProzineWins, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: HugoAwardBestProzineWins Context triple: [Worlds of If, HugoAwardBestProzineWins, 3]
-
A.
HugoAwardBestGraphicStoryWins
Indicates that an entity has won the Hugo Award for Best Graphic Story.
-
B.
numberOfHugoAwardsForBestProfessionalEditor
Indicates the count of Hugo Awards received for the role of Best Professional Editor.
-
C.
award for dramatic presentation in speculative fiction media
Indicates that an entity confers or is associated with a prize recognizing excellence in a dramatic work within speculative fiction media (such as science fiction, fantasy, or related genres).
-
D.
novelAward
Indicates that an entity has received an award specifically for a novel.
-
E.
awardWithinFiction
Indicates that an award is given or exists within a fictional context or narrative world, rather than in real life.
- 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_69f077ee19f881909af48f9cab00a2e5 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f65fe293188190a510c1d54a2bf542 |
completed | May 2, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69f659d297cc8190b2b962ba30a1edb3 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65ad638ac8190a17bb987fce53279 |
completed | May 2, 2026, 8:13 p.m. |
Created at: April 28, 2026, 9:46 a.m.