Triple

T36884606
Position Surface form Disambiguated ID Type / Status
Subject Crash Tag Team Racing E911573 entity
Predicate setting P1957 FINISHED
Object Von Clutch's MotorWorld
Von Clutch's MotorWorld is a sprawling, theme-park-style racing hub filled with diverse tracks, attractions, and characters in the Crash Bandicoot universe.
E2202631 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: Von Clutch's MotorWorld | Statement: [Crash Tag Team Racing, setting, Von Clutch's MotorWorld]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Von Clutch's MotorWorld
Triple: [Crash Tag Team Racing, setting, Von Clutch's MotorWorld]
Generated description
Von Clutch's MotorWorld is a sprawling, theme-park-style racing hub filled with diverse tracks, attractions, and characters in the Crash Bandicoot universe.

Provenance (5 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_69f76e8335908190b77e7e11d0e80820 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fd6c7c308190b22cb250d2903fd0 completed May 5, 2026, 2:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dfaf05d4c81908235acb6b2b9f06d completed June 26, 2026, 4:07 a.m.
NEDg Description generation batch_6a3dfed5ccc88190955bc6286e26a1a6 completed June 26, 2026, 4:23 a.m.
NED2 Entity disambiguation (via description) batch_6a3e039e01f48190a7cc4b4bd1e67ccd completed June 26, 2026, 4:44 a.m.
Created at: May 3, 2026, 4:13 p.m.