Triple

T37056038
Position Surface form Disambiguated ID Type / Status
Subject Taxi Driver E917187 entity
Predicate hasTrack P3284 FINISHED
Object Kid Nothing vs. the Echo Factor
"Kid Nothing vs. the Echo Factor" is a track by the experimental hip hop artist Taxi Driver, known for its abstract lyricism and unconventional production.
 E2210752 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: Kid Nothing vs. the Echo Factor | Statement: [Taxi Driver, hasTrack, Kid Nothing vs. the Echo Factor]
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: Kid Nothing vs. the Echo Factor
Triple: [Taxi Driver, hasTrack, Kid Nothing vs. the Echo Factor]
Generated description
"Kid Nothing vs. the Echo Factor" is a track by the experimental hip hop artist Taxi Driver, known for its abstract lyricism and unconventional production.

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_69f76e94d0308190a3f06890e133c88e completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb2f6a28588190931da28eb143e61d completed May 6, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e8c4f215881908c098be04fa80974 completed June 26, 2026, 2:27 p.m.
NEDg Description generation batch_6a3e988bb23481909963ddfe69b94bb8 completed June 26, 2026, 3:19 p.m.
NED2 Entity disambiguation (via description) batch_6a3ea842d27081908196f26e03a357cf completed June 26, 2026, 4:26 p.m.
Created at: May 3, 2026, 4:14 p.m.