Triple
T1436899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satyajit Ray |
E30576
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Calcutta |
E4838
|
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: Calcutta | Statement: [Satyajit Ray, workLocation, Calcutta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Calcutta Context triple: [Satyajit Ray, workLocation, Calcutta]
-
A.
Calcutta
chosen
Calcutta, now known as Kolkata, is a major cultural and commercial metropolis in eastern India that served as the capital of British India until the early 20th century.
-
B.
Chandannagar
Chandannagar is a former French colonial town in West Bengal, India, known for its historic riverside architecture and cultural blend of French and Bengali influences.
-
C.
Mumbai
Mumbai is a densely populated coastal metropolis in western India that serves as the country’s financial hub and the center of its film industry, Bollywood.
-
D.
Serampore
Serampore is a historic town on the Hooghly River in West Bengal, India, known for its colonial-era architecture and as a former Danish trading settlement.
-
E.
Kolkata Cantonment
Kolkata Cantonment is a major military cantonment area in Kolkata, India, housing key army installations and administrative facilities.
- 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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c50418d08190ace2cab98af87f29 |
completed | March 1, 2026, 11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aea82cd9748190ac82c7221455b2d5 |
completed | March 9, 2026, 10:59 a.m. |
Created at: March 1, 2026, 8 p.m.