Triple
T56288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hugo Award |
E1113
|
entity |
| Predicate | hasCategory |
P87
|
FINISHED |
| Object | Best Novelette |
E1113
|
NE 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: Best Novelette | Statement: [Hugo Award, hasCategory, Best Novelette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Best Novelette Context triple: [Hugo Award, hasCategory, Best Novelette]
-
A.
Locus Award
The Locus Award is a prestigious set of annual science fiction and fantasy literary awards voted on by readers of Locus magazine.
-
B.
Hugo Award
chosen
The Hugo Award is one of the most prestigious honors in science fiction and fantasy, recognizing outstanding works and achievements in the genre as voted on by members of the World Science Fiction Society.
-
C.
Ellie Awards
The Ellie Awards are prestigious annual honors recognizing excellence in American magazine journalism and publishing.
-
D.
Loveless Award
The Loveless Award is an honor recognizing significant contributions to the field of computing and information technology.
-
E.
Toppan Prize
The Toppan Prize is a prestigious academic award at Harvard University recognizing outstanding doctoral dissertations in the social sciences.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24b07f4a881909e32115e84da02a3 |
completed | Feb. 28, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a25ab7ec3881909356c659f4664fb8 |
completed | Feb. 28, 2026, 3:02 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.