Triple
T3777115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kim Kardashian: Hollywood |
E83333
|
entity |
| Predicate | gameplayFocus |
P31
|
FINISHED |
| Object | celebrity lifestyle simulation |
—
|
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: celebrity lifestyle simulation | Statement: [Kim Kardashian: Hollywood, gameplayFocus, celebrity lifestyle simulation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gameplayFocus Context triple: [Kim Kardashian: Hollywood, gameplayFocus, celebrity lifestyle simulation]
-
A.
homeGamesFocus
Indicates a focus or emphasis on games played at a team's home venue rather than away or neutral-site games.
-
B.
gameContext
Indicates the situational framework or environment in which a game’s actions, rules, and interactions take place.
-
C.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
D.
primaryGameMode
Indicates the main or default game mode associated with a particular game or gaming context.
-
E.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
- 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_69ad8b235e608190b5a2b1d1bfcef50b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc5d3dbc8190b6ab118a56acd5a3 |
completed | March 8, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_69adc050cc5c81909d9855f866f3c26d |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:36 p.m.