Triple

T36884604
Position Surface form Disambiguated ID Type / Status
Subject Crash Tag Team Racing E911573 entity
Predicate character P662 FINISHED
Object Pasadena O'Possum
Pasadena O'Possum is a southern-accented, sharpshooting opossum racer introduced as a new playable character in the Crash Bandicoot spin-off game Crash Tag Team Racing.
E2202629 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: Pasadena O'Possum | Statement: [Crash Tag Team Racing, character, Pasadena O'Possum]
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: Pasadena O'Possum
Triple: [Crash Tag Team Racing, character, Pasadena O'Possum]
Generated description
Pasadena O'Possum is a southern-accented, sharpshooting opossum racer introduced as a new playable character in the Crash Bandicoot spin-off game Crash Tag Team Racing.

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.