Triple
T33142357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | نهر جيحون |
E848189
|
entity |
| Predicate | اللغة_التي_يُستخدم_فيها_الاسم |
P15
|
FINISHED |
| Object | العربية |
—
|
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: العربية | Statement: [نهر جيحون, اللغة_التي_يُستخدم_فيها_الاسم, العربية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: اللغة_التي_يُستخدم_فيها_الاسم Context triple: [نهر جيحون, اللغة_التي_يُستخدم_فيها_الاسم, العربية]
-
A.
languageOfWorkOrName
chosen
Indicates the language in which a work is created or a name is expressed.
-
B.
languageName
Indicates the specific name assigned to a language in the relationship.
-
C.
languageOfNamesake
Indicates the language in which the namesake of an entity (such as a person, place, or object) is named or expressed.
-
D.
alternateLanguageName
Indicates that an entity has an additional name or label in a different language from its primary or default name.
-
E.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
- 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_69f3495961d88190b16ea542c2c5f825 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6db6af1d88190989810182354d60f |
completed | May 3, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69f6d82d068c8190940a3200ed760e38 |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:28 a.m.