Triple
T10213306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rangeela |
E242381
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object |
Mangta Hai Kya
"Mangta Hai Kya" is a popular Hindi song from the 1995 Bollywood film *Rangeela*, known for its catchy tune and A. R. Rahman’s distinctive music composition.
|
E849936
|
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: Mangta Hai Kya | Statement: [Rangeela, notableSong, Mangta Hai Kya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mangta Hai Kya Context triple: [Rangeela, notableSong, Mangta Hai Kya]
-
A.
Marga Marga
Marga Marga is a river in central Chile whose name was adopted by the surrounding Province of Marga Marga.
-
B.
Ko Haa
Ko Haa is a small group of picturesque limestone islets in southern Thailand known for their clear waters, coral reefs, and popular diving and snorkeling sites.
-
C.
Manjai Kunda
Manjai Kunda is a residential neighborhood within the urban area of Serekunda in The Gambia.
-
D.
Marda Kunama
Marda Kunama is a regional dialect of the Kunama language spoken by the Kunama people of the Horn of Africa.
-
E.
Mandara Manjari
Mandara Manjari is a philosophical work by the Dvaita Vedanta scholar Vyasatirtha, known for its exposition and defense of Madhva’s dualistic interpretation of Vedanta.
- 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: Mangta Hai Kya Triple: [Rangeela, notableSong, Mangta Hai Kya]
Generated description
"Mangta Hai Kya" is a popular Hindi song from the 1995 Bollywood film *Rangeela*, known for its catchy tune and A. R. Rahman’s distinctive music composition.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mangta Hai Kya Target entity description: "Mangta Hai Kya" is a popular Hindi song from the 1995 Bollywood film *Rangeela*, known for its catchy tune and A. R. Rahman’s distinctive music composition.
-
A.
Marga Marga
Marga Marga is a river in central Chile whose name was adopted by the surrounding Province of Marga Marga.
-
B.
Ko Haa
Ko Haa is a small group of picturesque limestone islets in southern Thailand known for their clear waters, coral reefs, and popular diving and snorkeling sites.
-
C.
Manjai Kunda
Manjai Kunda is a residential neighborhood within the urban area of Serekunda in The Gambia.
-
D.
Marda Kunama
Marda Kunama is a regional dialect of the Kunama language spoken by the Kunama people of the Horn of Africa.
-
E.
Mandara Manjari
Mandara Manjari is a philosophical work by the Dvaita Vedanta scholar Vyasatirtha, known for its exposition and defense of Madhva’s dualistic interpretation of Vedanta.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa24efc081909714d98943543283 |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d652ea80dc81908bc65ee2ec390467 |
completed | April 8, 2026, 1:06 p.m. |
| NEDg | Description generation | batch_69d657818b008190a24170717cff53b9 |
completed | April 8, 2026, 1:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d65835a11c819083d069ab0f644d4c |
completed | April 8, 2026, 1:29 p.m. |
Created at: April 6, 2026, 11:03 a.m.