Triple
T12490816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YBNL (album) |
E298555
|
entity |
| Predicate | hasGuestAppearance |
P4920
|
FINISHED |
| Object |
Base One
Base One is a Nigerian rapper known for his energetic Yoruba-infused hip-hop style and collaborations within the Afrobeats and street-rap scenes.
|
E988130
|
NE FINISHED |
How this triple was built (4 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: Base One | Statement: [YBNL (album), hasGuestAppearance, Base One]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Base One Context triple: [YBNL (album), hasGuestAppearance, Base One]
-
A.
Hub One
Hub One is a French digital services and telecommunications company specializing in connectivity, mobility, and IT solutions, particularly for airport and logistics environments.
-
B.
Base
Base is Julia’s core standard library module that provides fundamental language functionality, built-in types, and essential operations.
-
C.
Base
Base is LibreOffice’s database management application, used to create, manage, and query databases through a graphical interface.
-
D.
Year One
Year One is a 2009 comedy film directed by Harold Ramis that follows two primitive men on a biblical-era adventure, starring Jack Black and Michael Cera.
-
E.
CK One
CK One is a unisex fragrance by Calvin Klein known for its clean, fresh, and minimalist scent that became iconic in the 1990s.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Base One Triple: [YBNL (album), hasGuestAppearance, Base One]
Generated description
Base One is a Nigerian rapper known for his energetic Yoruba-infused hip-hop style and collaborations within the Afrobeats and street-rap scenes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Base One Target entity description: Base One is a Nigerian rapper known for his energetic Yoruba-infused hip-hop style and collaborations within the Afrobeats and street-rap scenes.
-
A.
Hub One
Hub One is a French digital services and telecommunications company specializing in connectivity, mobility, and IT solutions, particularly for airport and logistics environments.
-
B.
Base
Base is Julia’s core standard library module that provides fundamental language functionality, built-in types, and essential operations.
-
C.
Base
Base is LibreOffice’s database management application, used to create, manage, and query databases through a graphical interface.
-
D.
Year One
Year One is a 2009 comedy film directed by Harold Ramis that follows two primitive men on a biblical-era adventure, starring Jack Black and Michael Cera.
-
E.
CK One
CK One is a unisex fragrance by Calvin Klein known for its clean, fresh, and minimalist scent that became iconic in the 1990s.
- F. None of above. chosen
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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94de3076c81909640c982d520ca6b |
completed | April 10, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64ba9e1108190b74984d9da9baebe |
completed | May 2, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f64c535c9881908e5bf07d13fa73c5 |
completed | May 2, 2026, 7:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6508afef08190ac7a19b1ee90141e |
completed | May 2, 2026, 7:29 p.m. |
Created at: April 8, 2026, 9:56 p.m.