Triple
T7816061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rituparno Ghosh |
E181008
|
entity |
| Predicate | workedInLanguage |
P45484
|
FINISHED |
| Object | Bengali |
—
|
LITERAL 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: Bengali | Statement: [Rituparno Ghosh, workedInLanguage, Bengali]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workedInLanguage Context triple: [Rituparno Ghosh, workedInLanguage, Bengali]
-
A.
hasWorkedInLanguage
chosen
Indicates that an entity has performed work or professional activities using a particular language.
-
B.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
C.
workedAs
Indicates that an entity held a particular job, role, or position, performing work in that capacity.
-
D.
isWorkingLanguageOf
Indicates that a particular language is officially used as a medium of work, communication, or operation within a specified organization, institution, or context.
-
E.
hasWorkedIn
Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
- F. None of above.
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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf96d1f088190a1d005ffb019afe9 |
completed | March 30, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69cae91687788190af9cb7aaa996d291 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:39 p.m.