Triple
T31399332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | واسی |
E800949
|
entity |
| Predicate | زبانهای_در_تماس |
P95982
|
FINISHED |
| Object | دری |
—
|
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: دری | Statement: [واسی, زبانهای_در_تماس, دری]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: زبانهای_در_تماس Context triple: [واسی, زبانهای_در_تماس, دری]
-
A.
languageContactWith
Indicates a relationship where two or more languages come into contact through their speakers, leading to interaction and potential mutual influence.
-
B.
usedAsContactLanguageBetween
Indicates that a language functions as the medium of communication between two or more distinct language communities.
-
C.
linguisticallyRelatedTo
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
D.
hasContactWithLanguage
chosen
Indicates that an entity has some form of interaction, exposure, or engagement with a particular language.
-
E.
closelyAssociatedLanguage
Indicates that one language is closely connected to another, such as through frequent co-use, mutual influence, or strong cultural or regional association.
- 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_69f224ea9998819086ae2e4f4f4091c8 |
completed | April 29, 2026, 3:34 p.m. |
| NER | Named-entity recognition | batch_69f6a5f71b2c8190aade8a83f465be0c |
completed | May 3, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69f69fe66df08190958558d63ee623d9 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 29, 2026, 9:19 p.m.