Triple
T20419856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nitish Kumar |
E500816
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
Nishant Kumar
Nishant Kumar is known as the son of Indian politician and longtime Bihar Chief Minister Nitish Kumar.
|
E1436679
|
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: Nishant Kumar | Statement: [Nitish Kumar, child, Nishant Kumar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nishant Kumar Context triple: [Nitish Kumar, child, Nishant Kumar]
-
A.
Nish Kumar
Nish Kumar is a British stand-up comedian, actor, and radio presenter known for his sharp political satire and appearances on various UK comedy shows.
-
B.
Abhishek Verma
Abhishek Verma is a computer scientist best known as a co-creator of Google Borg, the large-scale cluster management and scheduling system that inspired Kubernetes.
-
C.
Gautam Kumar
Gautam Kumar is known as the son of legendary Indian Bengali actor Uttam Kumar.
-
D.
Shashank Manohar
Shashank Manohar is an Indian cricket administrator and lawyer who has served as president of the BCCI and later became a leading reformist figure in global cricket governance.
-
E.
Kumar Saurabh
Kumar Saurabh is a technology entrepreneur best known as a co-founder of the cloud-based machine data analytics company Sumo Logic.
- 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: Nishant Kumar Triple: [Nitish Kumar, child, Nishant Kumar]
Generated description
Nishant Kumar is known as the son of Indian politician and longtime Bihar Chief Minister Nitish Kumar.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nishant Kumar Target entity description: Nishant Kumar is known as the son of Indian politician and longtime Bihar Chief Minister Nitish Kumar.
-
A.
Nish Kumar
Nish Kumar is a British stand-up comedian, actor, and radio presenter known for his sharp political satire and appearances on various UK comedy shows.
-
B.
Abhishek Verma
Abhishek Verma is a computer scientist best known as a co-creator of Google Borg, the large-scale cluster management and scheduling system that inspired Kubernetes.
-
C.
Gautam Kumar
Gautam Kumar is known as the son of legendary Indian Bengali actor Uttam Kumar.
-
D.
Shashank Manohar
Shashank Manohar is an Indian cricket administrator and lawyer who has served as president of the BCCI and later became a leading reformist figure in global cricket governance.
-
E.
Kumar Saurabh
Kumar Saurabh is a technology entrepreneur best known as a co-founder of the cloud-based machine data analytics company Sumo Logic.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67ba39f7081909358f1103a0f241c |
completed | April 20, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08a551c6d0819097d11c928c505e58 |
completed | May 16, 2026, 5:11 p.m. |
| NEDg | Description generation | batch_6a08a6526fac81909c85dd3328722cec |
completed | May 16, 2026, 5:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08a6b8a6e081909cb691d71a1b2370 |
completed | May 16, 2026, 5:17 p.m. |
Created at: April 16, 2026, 11:30 a.m.