Triple
T25654927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Bengal Rahasya |
E643206
|
entity |
| Predicate | alternateNameOfProtagonist |
P46224
|
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: [Royal Bengal Rahasya, alternateNameOfProtagonist, Feluda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alternateNameOfProtagonist Context triple: [Royal Bengal Rahasya, alternateNameOfProtagonist, Feluda]
-
A.
protagonistAlsoKnownAs
chosen
Indicates that an entity serving as a protagonist is alternatively referred to by another name or alias.
-
B.
protagonistAlterEgoOf
Indicates that one entity is the alternate identity or secret persona of the main character (protagonist) in a narrative.
-
C.
characterAlias
Indicates that one character is known or referred to by an alternative name or alias.
-
D.
protagonistFullName
Indicates that the subject entity is the full, proper name (including given and family names) of the story’s main protagonist.
-
E.
protagonistDefaultName
Indicates that an entity is the default or canonical name assigned to the protagonist in a given work or context.
- 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_69e77e7d8a848190a98d0162325fd780 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f600c18a14819081b5914dd3b0f9cf |
completed | May 2, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fba5248190945acf1561280799 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 21, 2026, 6:31 p.m.