Triple
T19646363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | زَيْن |
E471681
|
entity |
| Predicate | معنى |
P102770
|
FINISHED |
| Object | الحُسن |
—
|
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: الحُسن | Statement: [زَيْن, معنى, الحُسن]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: معنى Context triple: [زَيْن, معنى, الحُسن]
-
A.
logicalMeaning
Indicates that one entity expresses, encodes, or conveys the logical content, implication, or formal meaning of another.
-
B.
meaningStatus
Indicates the relationship between an entity and the status of its meaning, such as whether its meaning is defined, clear, ambiguous, or unknown.
-
C.
stringMeaning
Indicates that one entity represents the semantic content or interpretation of a given string associated with another entity.
-
D.
meaningInContext
chosen
Indicates that one entity represents or conveys a particular meaning, interpretation, or sense within a specific context or situation.
-
E.
meaningViaAndrzej
Indicates that something’s meaning or interpretation is conveyed, mediated, or understood specifically through Andrzej.
- 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641250e108190a707452fefc87041 |
completed | April 20, 2026, 3:07 p.m. |
| PD | Predicate disambiguation | batch_69e514e941008190898d978d7bde91e4 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:44 p.m.