Triple
T7694411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deepika Padukone |
E174333
|
entity |
| Predicate | raisedIn |
P7868
|
FINISHED |
| Object | Bangalore, India |
E12663
|
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: Bangalore, India | Statement: [Deepika Padukone, raisedIn, Bangalore, India]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bangalore, India Context triple: [Deepika Padukone, raisedIn, Bangalore, India]
-
A.
Bengaluru
chosen
Bengaluru is a major Indian metropolis known as the country’s leading technology and innovation hub, often called the “Silicon Valley of India.”
-
B.
New Delhi, India
New Delhi, India is the capital city of India, serving as the nation’s political and administrative center and home to key government institutions and historic landmarks.
-
C.
Madras, India
Madras, India—now known as Chennai—is a major coastal metropolis in South India and the capital of the state of Tamil Nadu.
-
D.
Mambai
Mambai is an Austronesian language spoken primarily in East Timor, where it is one of the country’s major indigenous languages.
-
E.
Hyderabad
Hyderabad is a major city in southern India known for its historic Charminar monument, rich Hyderabadi cuisine, and growing technology industry.
- 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_69c6995966348190939e6c37ba272c06 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702459f988190bf7087bf51d5317f |
completed | March 27, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8acaa6004819088f1ae45ad9b378e |
completed | March 29, 2026, 4:38 a.m. |
Created at: March 27, 2026, 4:02 p.m.