Triple
T19358324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Meets East |
E484207
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Swara-Kakali
Swara-Kakali is a musical work or movement featured within the cross-cultural album or composition "West Meets East."
|
E1371670
|
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: Swara-Kakali | Statement: [West Meets East, hasPart, Swara-Kakali]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Swara-Kakali Context triple: [West Meets East, hasPart, Swara-Kakali]
-
A.
Narthaki
Narthaki is a small settlement in central Greece, located in the regional unit of Larissa within the historical region of Thessaly.
-
B.
Umka
Umka is a suburban settlement of Belgrade, Serbia, situated within the municipality of Čukarica along the right bank of the Sava River.
-
C.
Ketaki
Ketaki is a central female character in Rabindranath Tagore’s novel "Shesher Kobita," known for her modern outlook and complex romantic relationship with the protagonist, Amit.
-
D.
Chandramukhi
Chandramukhi is a courtesan and one of the central tragic figures in Sarat Chandra Chattopadhyay’s novel "Devdas," known for her deep, unrequited love and devotion to the protagonist.
-
E.
Chandramukhi
Chandramukhi is a hugely popular 2005 Tamil horror-comedy film that became one of Rajinikanth’s most successful and influential movies.
- 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: Swara-Kakali Triple: [West Meets East, hasPart, Swara-Kakali]
Generated description
Swara-Kakali is a musical work or movement featured within the cross-cultural album or composition "West Meets East."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Swara-Kakali Target entity description: Swara-Kakali is a musical work or movement featured within the cross-cultural album or composition "West Meets East."
-
A.
Narthaki
Narthaki is a small settlement in central Greece, located in the regional unit of Larissa within the historical region of Thessaly.
-
B.
Umka
Umka is a suburban settlement of Belgrade, Serbia, situated within the municipality of Čukarica along the right bank of the Sava River.
-
C.
Ketaki
Ketaki is a central female character in Rabindranath Tagore’s novel "Shesher Kobita," known for her modern outlook and complex romantic relationship with the protagonist, Amit.
-
D.
Chandramukhi
Chandramukhi is a courtesan and one of the central tragic figures in Sarat Chandra Chattopadhyay’s novel "Devdas," known for her deep, unrequited love and devotion to the protagonist.
-
E.
Chandramukhi
Chandramukhi is a hugely popular 2005 Tamil horror-comedy film that became one of Rajinikanth’s most successful and influential movies.
- 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_69d8e8d305088190ad13571532aa454c |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e6190a1ec88190ba6d2d45174dc85a |
completed | April 20, 2026, 12:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07240dacb881909a8acdb5dab42115 |
completed | May 15, 2026, 1:47 p.m. |
| NEDg | Description generation | batch_6a07253d53488190a25b4c65c93e70d7 |
completed | May 15, 2026, 1:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a072657035881909c63391b274063e1 |
completed | May 15, 2026, 1:57 p.m. |
Created at: April 10, 2026, 1:34 p.m.