Triple
T6478755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Digital Underground |
E146135
|
entity |
| Predicate | single |
P3283
|
FINISHED |
| Object |
No Nose Job
"No Nose Job" is a humorous hip-hop track by Digital Underground that satirically critiques beauty standards and cosmetic surgery.
|
E597044
|
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: No Nose Job | Statement: [Digital Underground, single, No Nose Job]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: No Nose Job Context triple: [Digital Underground, single, No Nose Job]
-
A.
Nose
Nose is a city in Osaka Prefecture, Japan, known for its rural landscapes, historic temples, and traditional countryside atmosphere.
-
B.
the Nose
The Nose is the absurd, anthropomorphized facial feature that becomes an independent character in Nikolai Gogol’s satirical short story of the same name.
-
C.
No Stylist
"No Stylist" is a 2018 hip-hop single by French Montana featuring Drake, known for its luxury-themed lyrics and high-profile collaboration.
-
D.
NO-DO
NO-DO was the official state-controlled newsreel service of Francoist Spain, used as a key propaganda tool in cinemas from the 1940s to the 1970s.
-
E.
No Air
"No Air" is a 2007 pop and R&B duet by Jordin Sparks and Chris Brown that became a major international hit known for its powerful vocals and emotional lyrics.
- 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: No Nose Job Triple: [Digital Underground, single, No Nose Job]
Generated description
"No Nose Job" is a humorous hip-hop track by Digital Underground that satirically critiques beauty standards and cosmetic surgery.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: No Nose Job Target entity description: "No Nose Job" is a humorous hip-hop track by Digital Underground that satirically critiques beauty standards and cosmetic surgery.
-
A.
Nose
Nose is a city in Osaka Prefecture, Japan, known for its rural landscapes, historic temples, and traditional countryside atmosphere.
-
B.
the Nose
The Nose is the absurd, anthropomorphized facial feature that becomes an independent character in Nikolai Gogol’s satirical short story of the same name.
-
C.
No Stylist
"No Stylist" is a 2018 hip-hop single by French Montana featuring Drake, known for its luxury-themed lyrics and high-profile collaboration.
-
D.
NO-DO
NO-DO was the official state-controlled newsreel service of Francoist Spain, used as a key propaganda tool in cinemas from the 1940s to the 1970s.
-
E.
No Air
"No Air" is a 2007 pop and R&B duet by Jordin Sparks and Chris Brown that became a major international hit known for its powerful vocals and emotional lyrics.
- 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_69c008fec7408190af7b146dc63d9750 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a4d35f08190a94143367b1d45c5 |
completed | March 22, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c653aa82808190a1e9d420e81d7839 |
completed | March 27, 2026, 9:53 a.m. |
| NEDg | Description generation | batch_69c6542017f4819085efe545dd25060f |
completed | March 27, 2026, 9:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c656d3533c819091a4255e354eccab |
completed | March 27, 2026, 10:07 a.m. |
Created at: March 22, 2026, 4:51 p.m.