Triple
T21944130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hindi Medium |
E541892
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object |
Sumit Arora
Sumit Arora is an Indian screenwriter best known for his work on the acclaimed Bollywood film "Hindi Medium."
|
E1522567
|
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: Sumit Arora | Statement: [Hindi Medium, writer, Sumit Arora]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sumit Arora Context triple: [Hindi Medium, writer, Sumit Arora]
-
A.
Vijay Arora
Vijay Arora is a cinematographer known for his work on the Hindi film "Shaadi No. 1."
-
B.
Ashok Arora
Ashok Arora is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
-
C.
Ashok Arora
Ashok Arora is an Indian entrepreneur best known as one of the co-founders of the global IT services and consulting company Infosys.
-
D.
Vijay Maurya
Vijay Maurya is an Indian actor, writer, and director known for his work in Hindi cinema and web series.
-
E.
Vipin Sharma
Vipin Sharma is an Indian actor known for his character roles in Hindi cinema and streaming projects, including a prominent part in the action thriller film "Monkey Man."
- 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: Sumit Arora Triple: [Hindi Medium, writer, Sumit Arora]
Generated description
Sumit Arora is an Indian screenwriter best known for his work on the acclaimed Bollywood film "Hindi Medium."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sumit Arora Target entity description: Sumit Arora is an Indian screenwriter best known for his work on the acclaimed Bollywood film "Hindi Medium."
-
A.
Vijay Arora
Vijay Arora is a cinematographer known for his work on the Hindi film "Shaadi No. 1."
-
B.
Ashok Arora
Ashok Arora is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
-
C.
Ashok Arora
Ashok Arora is an Indian entrepreneur best known as one of the co-founders of the global IT services and consulting company Infosys.
-
D.
Vijay Maurya
Vijay Maurya is an Indian actor, writer, and director known for his work in Hindi cinema and web series.
-
E.
Vipin Sharma
Vipin Sharma is an Indian actor known for his character roles in Hindi cinema and streaming projects, including a prominent part in the action thriller film "Monkey Man."
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242515ec8190b015bf8c7b13be85 |
completed | April 28, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a9eaa53cc8190bfc006245a63f9e5 |
completed | May 18, 2026, 5:07 a.m. |
| NEDg | Description generation | batch_6a0aa0066d0481909872d8e1dbbe2fcf |
completed | May 18, 2026, 5:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0aa07acd5c8190bc73cc1d8897fa01 |
completed | May 18, 2026, 5:15 a.m. |
Created at: April 16, 2026, 7:56 p.m.