Triple
T22292269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Court |
E551026
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Usha Bane
Usha Bane is an Indian actress best known for her role in the acclaimed Marathi courtroom drama film "Court."
|
E1573317
|
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: Usha Bane | Statement: [Court, starring, Usha Bane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Usha Bane Context triple: [Court, starring, Usha Bane]
-
A.
Usha Arghya
Usha Arghya is the concluding early-morning offering to the rising sun goddess Usha during the final day of the Hindu festival Chhath Puja.
-
B.
Kusum Misra
Kusum Misra is known as the wife of Indian civil servant and former Principal Secretary to the Prime Minister, Nripendra Misra.
-
C.
Usha Kundu
Usha Kundu is a physician and philanthropist whose contributions to healthcare and medical education led to a medical college being named in her honor.
-
D.
Asha Sachdev
Asha Sachdev is an Indian film and television actress known for her supporting and character roles in Hindi cinema, particularly during the 1970s and 1980s.
-
E.
Usha Khanna
Usha Khanna is a pioneering Indian music director and playback singer, known as one of the first prominent female composers in Hindi cinema.
- 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: Usha Bane Triple: [Court, starring, Usha Bane]
Generated description
Usha Bane is an Indian actress best known for her role in the acclaimed Marathi courtroom drama film "Court."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Usha Bane Target entity description: Usha Bane is an Indian actress best known for her role in the acclaimed Marathi courtroom drama film "Court."
-
A.
Usha Arghya
Usha Arghya is the concluding early-morning offering to the rising sun goddess Usha during the final day of the Hindu festival Chhath Puja.
-
B.
Kusum Misra
Kusum Misra is known as the wife of Indian civil servant and former Principal Secretary to the Prime Minister, Nripendra Misra.
-
C.
Usha Kundu
Usha Kundu is a physician and philanthropist whose contributions to healthcare and medical education led to a medical college being named in her honor.
-
D.
Asha Sachdev
Asha Sachdev is an Indian film and television actress known for her supporting and character roles in Hindi cinema, particularly during the 1970s and 1980s.
-
E.
Usha Khanna
Usha Khanna is a pioneering Indian music director and playback singer, known as one of the first prominent female composers in Hindi cinema.
- 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_69e11e45fb848190a1b2ae21296e3a5f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1560d1ec48190ab86f158c94b677b |
completed | April 29, 2026, 12:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c306cc2a08190b99dfaea6c1b3edd |
completed | May 19, 2026, 9:42 a.m. |
| NEDg | Description generation | batch_6a0c3283a77081908369f2b8cb78c781 |
completed | May 19, 2026, 9:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c331f08248190a6fa671734fca280 |
completed | May 19, 2026, 9:53 a.m. |
Created at: April 16, 2026, 8:41 p.m.