Triple
T30801900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gorky 17 (Amiga port) |
E784390
|
entity |
| Predicate | originalGameGenre |
P83654
|
FINISHED |
| Object | tactical role-playing 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: tactical role-playing game | Statement: [Gorky 17 (Amiga port), originalGameGenre, tactical role-playing game]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalGameGenre Context triple: [Gorky 17 (Amiga port), originalGameGenre, tactical role-playing game]
-
A.
gameGenreContext
Indicates the genre or type of game associated with a given game entity or gaming context.
-
B.
gameGenreDeveloped
Indicates that a particular game genre has been created, defined, or developed by a specific entity (such as a person, team, or organization).
-
C.
websiteGenre
Indicates the thematic category or type of content that a website is primarily associated with.
-
D.
primaryGameType
chosen
Indicates the main category or type of game with which an entity is primarily associated.
-
E.
originGame
Indicates the game from which an entity, such as a character, item, or concept, originally comes.
- 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_69f224b3a7ec819096939414d103e31e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a006fe981488190b4287289a3327664 |
completed | May 10, 2026, 11:45 a.m. |
| PD | Predicate disambiguation | batch_6a006f6976ec8190ba2c04fbaa946345 |
completed | May 10, 2026, 11:43 a.m. |
Created at: April 29, 2026, 8:42 p.m.