Triple
T27254162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Purulia Government Medical College and Hospital |
E687565
|
entity |
| Predicate | languageOfLocalUse |
P115774
|
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: [Purulia Government Medical College and Hospital, languageOfLocalUse, Bengali]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfLocalUse Context triple: [Purulia Government Medical College and Hospital, languageOfLocalUse, Bengali]
-
A.
languageOfLocalization
Indicates the language into which something (such as software, content, or an interface) has been localized for use or display.
-
B.
languageUsedInLocality
chosen
Indicates that a particular language is used or spoken within a specific locality or geographic area.
-
C.
localLanguageName
Indicates the name of a language as it is written or referred to in its own local or native form.
-
D.
dominantLocalLanguage
Indicates that one language is the primary or most widely used language within a specific local area or community.
-
E.
languageOfSurroundingCountry
Indicates that a language is the primary or commonly used language in the country surrounding a given place or region.
- 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_69ef35567e808190a94458cd44ebff0c |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: April 27, 2026, 10:47 a.m.