Triple
T389176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thuluth script |
E8843
|
entity |
| Predicate | difficultyLevel |
P2406
|
FINISHED |
| Object | considered one of the most difficult Arabic scripts to master |
—
|
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: considered one of the most difficult Arabic scripts to master | Statement: [Thuluth script, difficultyLevel, considered one of the most difficult Arabic scripts to master]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: difficultyLevel Context triple: [Thuluth script, difficultyLevel, considered one of the most difficult Arabic scripts to master]
-
A.
difficulty
chosen
Indicates the level of challenge, complexity, or effort required to perform an action, solve a problem, or achieve a particular outcome.
-
B.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
-
C.
automationLevel
Indicates the degree to which a process, task, or system is performed automatically rather than manually.
-
D.
hasMeasurementDifficulty
Indicates that performing a measurement on something is challenging or problematic in some way.
-
E.
achievementLevel
Indicates the degree or extent to which an entity has attained a particular goal, standard, or performance outcome.
- 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec5988708190aa86d9460cecf050 |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e96960608190bdd342da9c5ddb5e |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.