Triple
T20351743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harano Sur |
E496027
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Namita Sinha
Namita Sinha is an actress known for her role in the Bengali film "Harano Sur."
|
E1429815
|
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: Namita Sinha | Statement: [Harano Sur, hasCastMember, Namita Sinha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namita Sinha Context triple: [Harano Sur, hasCastMember, Namita Sinha]
-
A.
Namita Gokhale
Namita Gokhale is an Indian writer, publisher, and literary curator best known for her novels and for shaping contemporary literary culture in India.
-
B.
Ritu Banga
Ritu Banga is an Indian-American businesswoman and co-founder of the talent advisory firm Zoomdojo, known also as the wife of Mastercard executive and World Bank president Ajay Banga.
-
C.
Rukmini Haran
Rukmini Haran is a devotional Assamese literary work by the saint-scholar Srimanta Sankardev, narrating the story of Rukmini and her marriage to Krishna.
-
D.
Anuradha Banerjee
Anuradha Banerjee is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Banerjee.
-
E.
Vyjayanti Iyer
Vyjayanti Iyer is a central character in the 1993 Hindi romantic comedy film "Hum Hain Rahi Pyar Ke," known for her spirited and endearing role in the story.
- 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: Namita Sinha Triple: [Harano Sur, hasCastMember, Namita Sinha]
Generated description
Namita Sinha is an actress known for her role in the Bengali film "Harano Sur."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Namita Sinha Target entity description: Namita Sinha is an actress known for her role in the Bengali film "Harano Sur."
-
A.
Namita Gokhale
Namita Gokhale is an Indian writer, publisher, and literary curator best known for her novels and for shaping contemporary literary culture in India.
-
B.
Ritu Banga
Ritu Banga is an Indian-American businesswoman and co-founder of the talent advisory firm Zoomdojo, known also as the wife of Mastercard executive and World Bank president Ajay Banga.
-
C.
Rukmini Haran
Rukmini Haran is a devotional Assamese literary work by the saint-scholar Srimanta Sankardev, narrating the story of Rukmini and her marriage to Krishna.
-
D.
Anuradha Banerjee
Anuradha Banerjee is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Banerjee.
-
E.
Vyjayanti Iyer
Vyjayanti Iyer is a central character in the 1993 Hindi romantic comedy film "Hum Hain Rahi Pyar Ke," known for her spirited and endearing role in the story.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67850ace48190b19aff5780fef7e8 |
completed | April 20, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a087b0f8e4481908002adb56848e3e6 |
completed | May 16, 2026, 2:11 p.m. |
| NEDg | Description generation | batch_6a088014c30c8190937586dc3f23862e |
completed | May 16, 2026, 2:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08810e37c08190bd7e8b584204064c |
completed | May 16, 2026, 2:37 p.m. |
Created at: April 16, 2026, 11:24 a.m.