Triple
T32683199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramgati Upazila |
E835642
|
entity |
| Predicate | hasPrimarySchoolLanguage |
P56
|
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: [Ramgati Upazila, hasPrimarySchoolLanguage, Bengali]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimarySchoolLanguage Context triple: [Ramgati Upazila, hasPrimarySchoolLanguage, Bengali]
-
A.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
-
B.
hasPrimaryTraditionalLanguage
Indicates that one entity is the main or principal traditional language associated with another entity.
-
C.
primaryLanguageOfInstruction
chosen
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
-
D.
hasPrimaryVernacularLanguageFamily
Indicates that an entity’s main vernacular language belongs to a specified language family.
-
E.
parentLanguage
Indicates that one language is the ancestral or source language from which another language is derived or historically developed.
- 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_69f3493211388190993801216afbc2a7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a00d8ba18808190976682088a02a9a8 |
completed | May 10, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_6a00d85fad64819084f424ec8ecd3b57 |
completed | May 10, 2026, 7:11 p.m. |
Created at: May 1, 2026, 1:09 a.m.