Triple
T26142256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Süleyman |
E659548
|
entity |
| Predicate | equivalentNameInArabicScript |
P125165
|
FINISHED |
| Object | سليمان |
—
|
NE NERFINISHED |
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: سليمان | Statement: [Süleyman, equivalentNameInArabicScript, سليمان]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentNameInArabicScript Context triple: [Süleyman, equivalentNameInArabicScript, سليمان]
-
A.
hasNameInArabic
Indicates that an entity is associated with a specific name expressed in the Arabic language.
-
B.
correspondsToInArabic
chosen
Indicates that one entity is the equivalent or matching counterpart of another entity specifically in the Arabic language.
-
C.
hasGivenNameFormInArabic
Indicates that an entity has a specific given-name form expressed in the Arabic language.
-
D.
nameInAramaic
Indicates that an entity has a specific name expressed in the Aramaic language.
-
E.
transliterationName
Indicates that one entity is the transliterated form of another entity’s name from one writing system into another.
- 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_69ee5bc496a88190af7deb7ab5e081de |
completed | April 26, 2026, 6:39 p.m. |
| NER | Named-entity recognition | batch_69f62d89b89c8190afb372a8172111e7 |
completed | May 2, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69f62c1379f08190836c3e02b0c892df |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 26, 2026, 8:20 p.m.