Triple

T31163225
Position Surface form Disambiguated ID Type / Status
Subject Magic E794395 entity
Predicate hasCoverVersion P11142 FINISHED
Object Selena Gomez & the Scene – Magic
"Selena Gomez & the Scene – Magic" is a pop song performed by Selena Gomez & the Scene, known for its upbeat, whimsical style and association with Disney Channel projects.
E1949602 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: Selena Gomez & the Scene – Magic | Statement: [Magic, hasCoverVersion, Selena Gomez & the Scene – Magic]
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: Selena Gomez & the Scene – Magic
Triple: [Magic, hasCoverVersion, Selena Gomez & the Scene – Magic]
Generated description
"Selena Gomez & the Scene – Magic" is a pop song performed by Selena Gomez & the Scene, known for its upbeat, whimsical style and association with Disney Channel projects.

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_69f224d504908190b01278dcb7fc3fa7 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6984f709081908f2879f0cd1f4d6a completed May 3, 2026, 12:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a29472cd1ac819083bd5a545be51035 completed June 10, 2026, 11:14 a.m.
NEDg Description generation batch_6a2947e26f408190a9bc961974014450 completed June 10, 2026, 11:17 a.m.
NED2 Entity disambiguation (via description) batch_6a294eea0f148190a57b7ab05b9f0227 completed June 10, 2026, 11:47 a.m.
Created at: April 29, 2026, 9:07 p.m.