Triple
T36427480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | سورة الحجرات |
E897340
|
entity |
| Predicate | لغتها |
P4185
|
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: [سورة الحجرات, لغتها, العربية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: لغتها Context triple: [سورة الحجرات, لغتها, العربية]
-
A.
isLanguageOf
chosen
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
B.
hasLanguageInUniverse
Indicates that a particular language exists or is used within a specified fictional or conceptual universe.
-
C.
targetsLanguage
Indicates that an action, resource, or entity is specifically directed toward, designed for, or intended to be used with a particular language.
-
D.
мова
Indicates that an entity uses, is expressed in, or is associated with a particular language.
-
E.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
- 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_69f76e559b10819099d6655a6e14587c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.