Triple
T27079010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bibhu Bhattacharya |
E685541
|
entity |
| Predicate | characterPortrayedBelongsToSeries |
P178008
|
FINISHED |
| Object | Feluda |
—
|
NE NERFINISHED |
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: Feluda | Statement: [Bibhu Bhattacharya, characterPortrayedBelongsToSeries, Feluda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPortrayedBelongsToSeries Context triple: [Bibhu Bhattacharya, characterPortrayedBelongsToSeries, Feluda]
-
A.
characterPortrayedIs
Indicates that one entity serves as the fictional or dramatic role that is depicted or played by another entity.
-
B.
characterInFilmSeries
chosen
Indicates that a character appears in or is part of the cast of a particular film series.
-
C.
characterAffiliationPortrayed
Indicates that a portrayal shows a character as being affiliated with a particular group, organization, or side.
-
D.
laterPortrayedAs
Indicates that an entity is subsequently depicted or represented as another character, role, or form in a later work or context.
-
E.
characterPortrayedInYear
Indicates that a particular character was portrayed in a specific year.
- 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_69ef14843b1481909d828b3d5a44550a |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f75dc25fa08190b371faf36d9fb72c |
completed | May 3, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f758586534819083e91172f4bf5098 |
completed | May 3, 2026, 2:14 p.m. |
Created at: April 27, 2026, 8:33 a.m.