Triple
T26210581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dharmathakur |
E655475
|
entity |
| Predicate | languageOfCultTexts |
P17914
|
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: [Dharmathakur, languageOfCultTexts, Bengali]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfCultTexts Context triple: [Dharmathakur, languageOfCultTexts, Bengali]
-
A.
languageOfSurroundingCulture
Indicates that one entity is the language predominantly used or characteristic of the surrounding culture associated with another entity.
-
B.
religiousTextLanguageOf
Indicates that a particular language is the language in which a given religious text is written or primarily expressed.
-
C.
languageOfMyths
Indicates that the subject is the language in which the myths associated with the object are told or recorded.
-
D.
languageOfWritings
chosen
Indicates that a specified language is the one in which certain writings or written works are composed.
-
E.
languageAndCultureDimension
Indicates a relationship where aspects of language are connected to, shaped by, or reflective of broader cultural dimensions or contexts.
- 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_69ee5b49adb4819086545280d4ef6337 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: April 26, 2026, 8:52 p.m.