Triple
T5114617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nabaneeta Dev Sen |
E115300
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Dev Sen |
E115300
|
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: Dev Sen | Statement: [Nabaneeta Dev Sen, familyName, Dev Sen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dev Sen Context triple: [Nabaneeta Dev Sen, familyName, Dev Sen]
-
A.
Dev Sen
chosen
Dev Sen is the family name of Nabaneeta Dev Sen, a prominent Indian poet, writer, and academic.
-
B.
Dileep Rao
Dileep Rao is an American actor known for his supporting roles in major films such as Avatar, Drag Me to Hell, and Inception.
-
C.
Deepak Nayyar
Deepak Nayyar is an Indian economist and academic known for his work on development economics and his leadership roles in major universities and international economic institutions.
-
D.
Sanjay Suri
Sanjay Suri is an Indian actor and film producer known for his work in Hindi cinema and independent films.
-
E.
Mihir Rakshit
Mihir Rakshit is an Indian economist known for his contributions to macroeconomic theory and policy analysis, and for his long association with leading academic institutions in 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75cd13a08190b53e67ba65333557 |
completed | March 20, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bebaadfaac8190aa0407196e5c4c20 |
completed | March 21, 2026, 3:35 p.m. |
Created at: March 20, 2026, 1:41 p.m.