Triple
T20417428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jhankaar Beats |
E500748
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object |
Suno Na
"Suno Na" is a popular Hindi song from the Bollywood film "Jhankaar Beats," known for its melodious composition and romantic lyrics.
|
E1428941
|
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: Suno Na | Statement: [Jhankaar Beats, notableSong, Suno Na]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suno Na Context triple: [Jhankaar Beats, notableSong, Suno Na]
-
A.
Sone
Sone is a Japanese surname borne by various notable figures in politics, arts, and sports.
-
B.
Sauti Sol
Sauti Sol is a Kenyan afro-pop band known for their rich vocal harmonies and fusion of traditional African rhythms with contemporary pop and R&B sounds.
-
C.
Nini
Nini is one of the five Fuwa mascots of the 2008 Beijing Summer Olympics, inspired by a swallow and symbolizing good luck and the host city's culture.
-
D.
Nini
Nini is a supporting character in *Moulin Rouge! The Musical*, portrayed as one of the club’s dancers and a confidante within the bohemian world of the Moulin Rouge.
-
E.
Ano Mera
Ano Mera is a traditional inland village on the Greek island of Mykonos, known for its quieter atmosphere, central square, and historic Panagia Tourliani monastery.
- 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: Suno Na Triple: [Jhankaar Beats, notableSong, Suno Na]
Generated description
"Suno Na" is a popular Hindi song from the Bollywood film "Jhankaar Beats," known for its melodious composition and romantic lyrics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Suno Na Target entity description: "Suno Na" is a popular Hindi song from the Bollywood film "Jhankaar Beats," known for its melodious composition and romantic lyrics.
-
A.
Sone
Sone is a Japanese surname borne by various notable figures in politics, arts, and sports.
-
B.
Sauti Sol
Sauti Sol is a Kenyan afro-pop band known for their rich vocal harmonies and fusion of traditional African rhythms with contemporary pop and R&B sounds.
-
C.
Nini
Nini is a supporting character in *Moulin Rouge! The Musical*, portrayed as one of the club’s dancers and a confidante within the bohemian world of the Moulin Rouge.
-
D.
Nini
Nini is one of the five Fuwa mascots of the 2008 Beijing Summer Olympics, inspired by a swallow and symbolizing good luck and the host city's culture.
-
E.
Ano Mera
Ano Mera is a traditional inland village on the Greek island of Mykonos, known for its quieter atmosphere, central square, and historic Panagia Tourliani monastery.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a44ecf48190ba5a3872af500dc8 |
completed | April 20, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a087b284bb8819090f76ec27116c619 |
completed | May 16, 2026, 2:11 p.m. |
| NEDg | Description generation | batch_6a088017be588190ab94b8180e44ebf4 |
completed | May 16, 2026, 2:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0880c45e1081908f439ade0c31a47e |
completed | May 16, 2026, 2:35 p.m. |
Created at: April 16, 2026, 11:30 a.m.