Triple
T22292119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinhasan |
E551023
|
entity |
| Predicate | authorOfSourceWork |
P2353
|
FINISHED |
| Object |
Arun Sadhu
Arun Sadhu was an Indian journalist, political commentator, and Marathi-English writer known for his incisive novels and works on contemporary socio-political issues.
|
E1556243
|
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: Arun Sadhu | Statement: [Sinhasan, authorOfSourceWork, Arun Sadhu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arun Sadhu Context triple: [Sinhasan, authorOfSourceWork, Arun Sadhu]
-
A.
Arun Shah
Arun Shah is an entrepreneur best known as one of the founders behind the global denim and casualwear brand Pepe Jeans.
-
B.
Arun Kumar
Arun Kumar is a film editor known for his work on the movie "Billu."
-
C.
Sanjay Sankla
Sanjay Sankla is an Indian film editor known for his work on Hindi cinema, including the popular film "Hum Hain Rahi Pyar Ke."
-
D.
Arun Tiwari
Arun Tiwari is an Indian missile scientist and author best known for co-authoring the autobiography "Wings of Fire" with A. P. J. Abdul Kalam.
-
E.
Satya Nandan
Satya Nandan was a Fijian diplomat and international lawyer renowned for his leading role in shaping the United Nations Convention on the Law of the Sea and in developing global ocean governance.
- 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: Arun Sadhu Triple: [Sinhasan, authorOfSourceWork, Arun Sadhu]
Generated description
Arun Sadhu was an Indian journalist, political commentator, and Marathi-English writer known for his incisive novels and works on contemporary socio-political issues.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Arun Sadhu Target entity description: Arun Sadhu was an Indian journalist, political commentator, and Marathi-English writer known for his incisive novels and works on contemporary socio-political issues.
-
A.
Arun Shah
Arun Shah is an entrepreneur best known as one of the founders behind the global denim and casualwear brand Pepe Jeans.
-
B.
Arun Kumar
Arun Kumar is a film editor known for his work on the movie "Billu."
-
C.
Sanjay Sankla
Sanjay Sankla is an Indian film editor known for his work on Hindi cinema, including the popular film "Hum Hain Rahi Pyar Ke."
-
D.
Arun Tiwari
Arun Tiwari is an Indian missile scientist and author best known for co-authoring the autobiography "Wings of Fire" with A. P. J. Abdul Kalam.
-
E.
Satya Nandan
Satya Nandan was a Fijian diplomat and international lawyer renowned for his leading role in shaping the United Nations Convention on the Law of the Sea and in developing global ocean governance.
- 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_6a0ba791d9ec81908a518673ed3dd04b |
completed | May 18, 2026, 11:58 p.m. |
| NEDg | Description generation | batch_6a0ba81bade88190bc0f4225600509a2 |
completed | May 19, 2026, midnight |
| NED2 | Entity disambiguation (via description) | batch_6a0ba8c3d6c88190944df9358dd58c4e |
completed | May 19, 2026, 12:03 a.m. |
Created at: April 16, 2026, 8:41 p.m.