Triple
T1745514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabic alphabet |
E38326
|
entity |
| Predicate | hasMedialForm |
P9189
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Arabic alphabet, hasMedialForm, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMedialForm Context triple: [Arabic alphabet, hasMedialForm, yes]
-
A.
hasContextualLetterForms
chosen
Indicates that the written form of a letter changes shape depending on its surrounding characters or position within a word.
-
B.
hasCaseForms
Indicates that an entity possesses multiple grammatical case variants or inflected forms associated with it.
-
C.
hasMasculineForm
Indicates that an entity has a corresponding masculine grammatical or lexical form.
-
D.
hasConjunctForms
Indicates that an entity is associated with one or more conjunct (combined or compound) forms of itself or related elements.
-
E.
hasConsonantGradation
Indicates that a word undergoes systematic alternation of its consonants (consonant gradation) in different morphological or phonological forms.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab630e7d008190a8c673665d9672bb |
completed | March 6, 2026, 11:28 p.m. |
| PD | Predicate disambiguation | batch_69aa61c5a18481909bc49e0c54d64314 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.