Triple
T2162496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chutney music |
E46831
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object |
Nani and Nana
"Nani and Nana" is a well-known chutney music song recognized for its catchy rhythm and popularity within Indo-Caribbean musical culture.
|
E239524
|
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: Nani and Nana | Statement: [Chutney music, notableSong, Nani and Nana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nani and Nana Context triple: [Chutney music, notableSong, Nani and Nana]
-
A.
Nana
Nana is an 1880 naturalist novel by Émile Zola that follows the rise and fall of a Parisian courtesan as a critique of Second Empire society.
-
B.
Nani
Nani is a Portuguese professional footballer best known as a dynamic winger who starred for Manchester United and the Portugal national team, winning multiple domestic titles and the UEFA Euro 2016.
-
C.
Nene
Nene was the principal wife of Japanese warlord Toyotomi Hideyoshi and a politically influential noblewoman during the late Sengoku period.
-
D.
Nena
Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
-
E.
Lili
Lili is a 1953 musical fantasy film starring Leslie Caron as a naive orphan who joins a carnival and forms a touching bond with a puppeteer.
- 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: Nani and Nana Triple: [Chutney music, notableSong, Nani and Nana]
Generated description
"Nani and Nana" is a well-known chutney music song recognized for its catchy rhythm and popularity within Indo-Caribbean musical culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nani and Nana Target entity description: "Nani and Nana" is a well-known chutney music song recognized for its catchy rhythm and popularity within Indo-Caribbean musical culture.
-
A.
Nana
Nana is an 1880 naturalist novel by Émile Zola that follows the rise and fall of a Parisian courtesan as a critique of Second Empire society.
-
B.
Nani
Nani is a Portuguese professional footballer best known as a dynamic winger who starred for Manchester United and the Portugal national team, winning multiple domestic titles and the UEFA Euro 2016.
-
C.
Nene
Nene was the principal wife of Japanese warlord Toyotomi Hideyoshi and a politically influential noblewoman during the late Sengoku period.
-
D.
Nena
Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
-
E.
Lili
Lili is a 1953 musical fantasy film starring Leslie Caron as a naive orphan who joins a carnival and forms a touching bond with a puppeteer.
- 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_69a88a184cbc8190877791f6552c2484 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe8b9c0881908373eabc7f81c394 |
completed | March 7, 2026, 5:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58ec0a7481909bc3e751de31e4d7 |
completed | March 9, 2026, 5:21 a.m. |
| NEDg | Description generation | batch_69ae59c3e0008190942715e0c44ca206 |
completed | March 9, 2026, 5:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5a446350819080cdacd9a98f8de2 |
completed | March 9, 2026, 5:27 a.m. |
Created at: March 4, 2026, 7:45 p.m.