Triple
T18165420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | وادي عربة |
E434879
|
entity |
| Predicate | اللغة الشائعة في جانبه الغربي |
P109219
|
FINISHED |
| Object | اللغة العبرية |
—
|
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: اللغة العبرية | Statement: [وادي عربة, اللغة الشائعة في جانبه الغربي, اللغة العبرية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: اللغة الشائعة في جانبه الغربي Context triple: [وادي عربة, اللغة الشائعة في جانبه الغربي, اللغة العبرية]
-
A.
hasLanguageOnEasternSide
chosen
Indicates that a specified language is used or spoken on the eastern side of a given area, boundary, or region.
-
B.
hasLanguageOfSide
Indicates that an entity uses or is associated with a particular language on a specific side or aspect (e.g., one side of a bilingual object or interface).
-
C.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
-
D.
primaryLanguageSide2
Indicates that the second entity in the relationship uses or is associated with the primary language specified.
-
E.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dec71b7881908d123d0cea3adf1f |
completed | April 19, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:30 a.m.