Triple
T31439225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koopley |
E802020
|
entity |
| Predicate | hasInGameModelType |
P2390
|
FINISHED |
| Object | paper-style 2D character |
—
|
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: paper-style 2D character | Statement: [Koopley, hasInGameModelType, paper-style 2D character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInGameModelType Context triple: [Koopley, hasInGameModelType, paper-style 2D character]
-
A.
hasModelType
chosen
Indicates that an entity is associated with or classified under a specific model type.
-
B.
hasGameType
Indicates that an entity (such as a game or match) is associated with a specific category or type of game.
-
C.
hasInGameItemType
Indicates that an entity possesses or is associated with a specific type or category of in-game item.
-
D.
hasModelIn
Indicates that an entity is represented or instantiated as a model within a specified context, system, or container.
-
E.
hasInGameCategory
Indicates that an in-game item, action, or entity belongs to a specific predefined category within the game’s classification system.
- 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_69f348c5a6bc819092a557e95438976f |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ff397e19a88190a945b826159f5290 |
completed | May 9, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69ff392400d0819088d30d08d4a774bd |
completed | May 9, 2026, 1:39 p.m. |
Created at: April 30, 2026, 9:04 p.m.