Triple
T33925362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | পৈরীমোহন |
E869734
|
entity |
| Predicate | উপন্যাসের_চরিত্র |
P83677
|
FINISHED |
| Object | গোরা |
—
|
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: গোরা | Statement: [পৈরীমোহন, উপন্যাসের_চরিত্র, গোরা]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: উপন্যাসের_চরিত্র Context triple: [পৈরীমোহন, উপন্যাসের_চরিত্র, গোরা]
-
A.
characters
chosen
Indicates that one entity is a character (or set of characters) associated with, appearing in, or belonging to another entity (such as a work, story, or medium).
-
B.
storyCharacterizedAs
Indicates that a story is described, portrayed, or defined as having a particular quality, style, or attribute.
-
C.
literaryCharacterModeledAs
Indicates that one literary character is created or portrayed based on the traits, life, or persona of another real or fictional individual.
-
D.
narrativeCharacter
Indicates that one entity functions as a character within the narrative or story associated with another entity.
-
E.
fictionalCharacter
Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
- 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_69f349992c508190aa4afa24a086cc8c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70b966860819089cf92927f47c5f1 |
completed | May 3, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69f70abe43e08190b2a30930d96247c1 |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:49 a.m.