Triple
T11252002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BAFTA Games Award for Best Game (for Dishonored) |
E266340
|
entity |
| Predicate | genreOfWorkAwarded |
P38820
|
FINISHED |
| Object | action-adventure game |
—
|
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: action-adventure game | Statement: [BAFTA Games Award for Best Game (for Dishonored), genreOfWorkAwarded, action-adventure game]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfWorkAwarded Context triple: [BAFTA Games Award for Best Game (for Dishonored), genreOfWorkAwarded, action-adventure game]
-
A.
genreOfWorkHonored
chosen
Indicates the specific genre or type of creative work for which an honor, award, or recognition is given.
-
B.
genreOfAwards
Indicates the type or category of awards associated with a given work, event, or entity.
-
C.
notableAwardWork
Indicates that a work is the specific creation (e.g., book, film, artwork) for which an award or honor was given.
-
D.
awardGenreFocus
Indicates that an award specifically recognizes or emphasizes works within a particular genre.
-
E.
genreOfWorkDirected
Indicates that a person has directed a work (such as a film, show, or performance) belonging to a specified genre.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e933648481909873094bc89ed041 |
completed | April 9, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69d78793c00481908a3f764b610b77a4 |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:31 p.m.