Triple
T11383573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anshu Jain |
E269657
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Anshu Jain |
E269657
|
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: Anshu Jain | Statement: [Anshu Jain, name, Anshu Jain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anshu Jain Context triple: [Anshu Jain, name, Anshu Jain]
-
A.
Anshu Jain
chosen
Anshu Jain was a prominent investment banker best known as the former co-CEO of Deutsche Bank and later a senior executive at Cantor Fitzgerald.
-
B.
Aseem Kishore
Aseem Kishore is a technology writer and blogger known for creating practical guides and tutorials on software, web development, and digital tools.
-
C.
Mukul Sharma
Mukul Sharma was an Indian writer, journalist, and science fiction author known for his popular science columns and for inspiring several acclaimed film adaptations.
-
D.
Shantanu Thakur
Shantanu Thakur is an Indian politician from the Bharatiya Janata Party who serves as a Minister of State in the central government and represents the Bangaon constituency in the Lok Sabha.
-
E.
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.
- 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7fc34f1f0819082dd977313ee6070 |
completed | April 9, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58c1d4b188190b83cfad0cc95483e |
completed | April 20, 2026, 2:14 a.m. |
Created at: April 8, 2026, 9:34 p.m.