Triple
T10262195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diplo |
E240624
|
entity |
| Predicate | notableSongProduced |
P8087
|
FINISHED |
| Object |
Close to Me
"Close to Me" is a 2018 electro-pop collaboration between Ellie Goulding, Diplo, and Swae Lee that blends catchy melodies with dance-oriented production.
|
E851681
|
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: Close to Me | Statement: [Diplo, notableSongProduced, Close to Me]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Close to Me Context triple: [Diplo, notableSongProduced, Close to Me]
-
A.
So Close
So Close is a popular song by South Korean singer JR, recognized as one of his standout solo releases.
-
B.
Too Close
"Too Close" is a 1998 R&B hit single by American group Next, best known for its sensual lyrics and chart-topping success.
-
C.
Too Close
"Too Close" is a 2011 electro-soul song by British singer Alex Clare that gained widespread popularity after being featured in a major Internet Explorer commercial.
-
D.
Come Close
"Come Close" is a soulful hip-hop single by Common, produced by The Neptunes and known for its intimate, romantic lyrics.
-
E.
Come Closer
"Come Closer" is a hit Afrobeats single by Nigerian artist Wizkid featuring Drake, known for its fusion of Afrobeat and dancehall and its international chart success.
- 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: Close to Me Triple: [Diplo, notableSongProduced, Close to Me]
Generated description
"Close to Me" is a 2018 electro-pop collaboration between Ellie Goulding, Diplo, and Swae Lee that blends catchy melodies with dance-oriented production.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Close to Me Target entity description: "Close to Me" is a 2018 electro-pop collaboration between Ellie Goulding, Diplo, and Swae Lee that blends catchy melodies with dance-oriented production.
-
A.
So Close
So Close is a popular song by South Korean singer JR, recognized as one of his standout solo releases.
-
B.
Too Close
"Too Close" is a 1998 R&B hit single by American group Next, best known for its sensual lyrics and chart-topping success.
-
C.
Too Close
"Too Close" is a 2011 electro-soul song by British singer Alex Clare that gained widespread popularity after being featured in a major Internet Explorer commercial.
-
D.
Come Close
"Come Close" is a soulful hip-hop single by Common, produced by The Neptunes and known for its intimate, romantic lyrics.
-
E.
Come Closer
"Come Closer" is a hit Afrobeats single by Nigerian artist Wizkid featuring Drake, known for its fusion of Afrobeat and dancehall and its international chart success.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d25c8dec8190af9160d9338ffc9c |
completed | April 7, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f7f81dd481909022efde8fc46e68 |
completed | April 9, 2026, 12:51 a.m. |
| NEDg | Description generation | batch_69d6fcabb5a08190a26c068163f48878 |
completed | April 9, 2026, 1:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6fd7212b88190b410b8e1cc6f56fd |
completed | April 9, 2026, 1:14 a.m. |
Created at: April 6, 2026, 11:32 a.m.