Triple

T26455942
Position Surface form Disambiguated ID Type / Status
Subject Fu-Schnickens E665484 entity
Predicate debutAlbum P3278 FINISHED
Object F.U. Don't Take It Personal
F.U. Don't Take It Personal is a 1992 hip hop album by Fu-Schnickens known for its fast-paced, tongue-twisting raps and playful, Afrocentric style.
E1725214 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: F.U. Don't Take It Personal | Statement: [Fu-Schnickens, debutAlbum, F.U. Don't Take It Personal]
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: F.U. Don't Take It Personal
Triple: [Fu-Schnickens, debutAlbum, F.U. Don't Take It Personal]
Generated description
F.U. Don't Take It Personal is a 1992 hip hop album by Fu-Schnickens known for its fast-paced, tongue-twisting raps and playful, Afrocentric style.

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_69ee883d5040819097dd154643005230 completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f61268e08c8190a29c2ae279d098d9 completed May 2, 2026, 3:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11aed92d7c81909169b1ce21ac0697 completed May 23, 2026, 1:42 p.m.
NEDg Description generation batch_6a11afcce63c8190ac822c630de91480 completed May 23, 2026, 1:46 p.m.
NED2 Entity disambiguation (via description) batch_6a11b08396c8819094b627b21872f43b completed May 23, 2026, 1:49 p.m.
Created at: April 27, 2026, 12:09 a.m.