Triple
T17395629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanya Dubash |
E422945
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Arun Phirojsha Nanda
Arun Phirojsha Nanda is an Indian businessman known for his leadership roles within the Godrej Group conglomerate.
|
E1266696
|
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 Phirojsha Nanda | Statement: [Tanya Dubash, spouse, Arun Phirojsha Nanda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arun Phirojsha Nanda Context triple: [Tanya Dubash, spouse, Arun Phirojsha Nanda]
-
A.
Ashok Chandra
Ashok Chandra is a computer scientist known for his contributions to theoretical computer science and complexity theory.
-
B.
Champai Soren
Champai Soren is an Indian politician from Jharkhand and a prominent leader of the Jharkhand Mukti Morcha (JMM).
-
C.
Bet Shankhodhar
Bet Shankhodhar is a small island off the coast of Gujarat, India, revered in Hindu tradition as the legendary dwelling place of Lord Krishna and a popular pilgrimage site.
-
D.
Kamu Mukherjee
Kamu Mukherjee was an Indian character actor known for his work in Bengali cinema, particularly in films by directors like Satyajit Ray.
-
E.
Premangshu Bose
Premangshu Bose is an actor known for his role in the Indian film "Nayak."
- 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 Phirojsha Nanda Triple: [Tanya Dubash, spouse, Arun Phirojsha Nanda]
Generated description
Arun Phirojsha Nanda is an Indian businessman known for his leadership roles within the Godrej Group conglomerate.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Arun Phirojsha Nanda Target entity description: Arun Phirojsha Nanda is an Indian businessman known for his leadership roles within the Godrej Group conglomerate.
-
A.
Ashok Chandra
Ashok Chandra is a computer scientist known for his contributions to theoretical computer science and complexity theory.
-
B.
Champai Soren
Champai Soren is an Indian politician from Jharkhand and a prominent leader of the Jharkhand Mukti Morcha (JMM).
-
C.
Bet Shankhodhar
Bet Shankhodhar is a small island off the coast of Gujarat, India, revered in Hindu tradition as the legendary dwelling place of Lord Krishna and a popular pilgrimage site.
-
D.
Kamu Mukherjee
Kamu Mukherjee was an Indian character actor known for his work in Bengali cinema, particularly in films by directors like Satyajit Ray.
-
E.
Premangshu Bose
Premangshu Bose is an actor known for his role in the Indian film "Nayak."
- 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_69d889d710288190bf0f4762801fefae |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43abcd8b081908579ee9a80f65802 |
completed | April 19, 2026, 2:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01a00100c48190930c8bf9b6917aa5 |
completed | May 11, 2026, 9:23 a.m. |
| NEDg | Description generation | batch_6a01a176d2488190951bbe07233a37e4 |
completed | May 11, 2026, 9:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01a58b12088190828078c69c4fff4b |
completed | May 11, 2026, 9:46 a.m. |
Created at: April 10, 2026, 5:45 a.m.