Triple
T25843637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | صاد |
E651003
|
entity |
| Predicate | يميز |
P159345
|
FINISHED |
| Object | معاني كلمات عربية عن نظائرها بحرف السين |
—
|
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: معاني كلمات عربية عن نظائرها بحرف السين | Statement: [صاد, يميز, معاني كلمات عربية عن نظائرها بحرف السين]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: يميز Context triple: [صاد, يميز, معاني كلمات عربية عن نظائرها بحرف السين]
-
A.
ظهرفي
Indicates that an entity appears, is shown, or is present within another entity (such as a place, medium, or context).
-
B.
מטרה
Indicates that an entity serves as the goal, aim, or intended target of another entity or action.
-
C.
მეუღლე
Indicates a spousal relationship between two people, where each is the legally or socially recognized husband or wife of the other.
-
D.
نوقشفي
Indicates that something or someone was discussed or debated within a particular context or setting.
-
E.
تصدر
Indicates that an entity issues, publishes, or comes out as something (e.g., a statement, decision, or item) in relation to another entity or context.
- F. None of above. chosen
Provenance (4 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_69e7ab38086081908f3a8e7e0c6efd83 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6023662a48190b8eb77eebc225c36 |
completed | May 2, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69f4938b960081909b53c074a3e0c7c2 |
completed | May 1, 2026, 11:50 a.m. |
| PDg | Predicate description generation | batch_69f497b8abb88190bb672cf6907c4b8d |
completed | May 1, 2026, 12:08 p.m. |
Created at: April 22, 2026, 7:51 a.m.