Triple
T2824092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruzena Bajcsy |
E54877
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object | Vijay Kumar |
E48405
|
NE FINISHED |
How this triple was built (2 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: Vijay Kumar | Statement: [Ruzena Bajcsy, notableStudent, Vijay Kumar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vijay Kumar Context triple: [Ruzena Bajcsy, notableStudent, Vijay Kumar]
-
A.
Vijay Kumar
chosen
Vijay Kumar is a prominent roboticist and engineer known for his pioneering work in multi-robot systems and aerial robotics.
-
B.
Nirvikar Singh
Nirvikar Singh is an economist and academic known for his contributions to economic theory and policy, associated with leading institutions such as the Delhi School of Economics.
-
C.
Yogendra Shukla
Yogendra Shukla was an Indian freedom fighter and revolutionary leader associated with the independence movement against British colonial rule.
-
D.
Satinder Singh
Satinder Singh is a computer scientist and researcher known for his contributions to reinforcement learning and artificial intelligence.
-
E.
Jagdeep Dhankhar
Jagdeep Dhankhar is an Indian politician and lawyer serving as the 14th Vice President of India.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ab49e100c0819082a40cb797383243 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde91487881909989c08bbf76f0da |
completed | March 7, 2026, 8:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afcead12588190bfbb2c9e93b05e0d |
completed | March 10, 2026, 7:56 a.m. |
Created at: March 6, 2026, 9:59 p.m.