Triple
T28083438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parthibo |
E709748
|
entity |
| Predicate | literaryLanguageRegion |
P170656
|
FINISHED |
| Object | West Bengal |
—
|
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: West Bengal | Statement: [Parthibo, literaryLanguageRegion, West Bengal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryLanguageRegion Context triple: [Parthibo, literaryLanguageRegion, West Bengal]
-
A.
literaryLanguage
Indicates that an entity is expressed, written, or communicated using a particular literary or standardized written language.
-
B.
languageArea
Indicates the geographic or cultural region in which a particular language is used or predominantly spoken.
-
C.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
D.
firstPublicationLanguageRegion
Indicates the geographic region associated with the language in which an entity was first published.
-
E.
alsoInLanguageRegion
Indicates that two or more entities are located within or associated with the same language-defined geographic region.
- F. None of above. chosen
Provenance (4 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_69ef9b7037f0819095bb90eaccbcaf32 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f693ffa7908190aa4c451b16df9be6 |
completed | May 3, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f6938244648190a553b532387b812c |
completed | May 3, 2026, 12:14 a.m. |
Created at: April 27, 2026, 8:53 p.m.