Triple
T8565367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baashha |
E202787
|
entity |
| Predicate | hasSong |
P20452
|
FINISHED |
| Object |
Naan Autokaaran
"Naan Autokaaran" is a popular Tamil song from the 1995 Rajinikanth film *Baashha*, known for its energetic music and iconic portrayal of the protagonist as an auto-rickshaw driver.
|
E742970
|
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: Naan Autokaaran | Statement: [Baashha, hasSong, Naan Autokaaran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naan Autokaaran Context triple: [Baashha, hasSong, Naan Autokaaran]
-
A.
L’Auto
L’Auto was a French sports newspaper best known for creating and organizing the Tour de France.
-
B.
Autokomanda
Autokomanda is a major traffic junction and neighborhood in Belgrade, Serbia, known for its busy interchange connecting several key city districts.
-
C.
Citura
Citura is the public transport operator responsible for managing Reims’ urban transit network, including its tramway system, in northeastern France.
-
D.
Gari
Gari is a celebrated Kannada literary work by the renowned poet D. R. Bendre.
-
E.
Bilen
Bilen is a Cushitic language spoken primarily by the Bilen people in central Eritrea.
- 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: Naan Autokaaran Triple: [Baashha, hasSong, Naan Autokaaran]
Generated description
"Naan Autokaaran" is a popular Tamil song from the 1995 Rajinikanth film *Baashha*, known for its energetic music and iconic portrayal of the protagonist as an auto-rickshaw driver.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Naan Autokaaran Target entity description: "Naan Autokaaran" is a popular Tamil song from the 1995 Rajinikanth film *Baashha*, known for its energetic music and iconic portrayal of the protagonist as an auto-rickshaw driver.
-
A.
L’Auto
L’Auto was a French sports newspaper best known for creating and organizing the Tour de France.
-
B.
Autokomanda
Autokomanda is a major traffic junction and neighborhood in Belgrade, Serbia, known for its busy interchange connecting several key city districts.
-
C.
Citura
Citura is the public transport operator responsible for managing Reims’ urban transit network, including its tramway system, in northeastern France.
-
D.
Gari
Gari is a celebrated Kannada literary work by the renowned poet D. R. Bendre.
-
E.
Bilen
Bilen is a Cushitic language spoken primarily by the Bilen people in central Eritrea.
- 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_69ca8327b0a881908606ff860713964d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe9d2331881909d92ddde90f580e9 |
completed | March 31, 2026, 3:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce89677888819091dfda14ce6baef3 |
completed | April 2, 2026, 3:21 p.m. |
| NEDg | Description generation | batch_69ce8c10d774819086437ffeeb1ef25d |
completed | April 2, 2026, 3:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce8d0064fc819095058293e4229f25 |
completed | April 2, 2026, 3:36 p.m. |
Created at: March 30, 2026, 6:20 p.m.