Triple
T1055502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bashkir language |
E22791
|
entity |
| Predicate | usedArabicAlphabet |
P7160
|
FINISHED |
| Object | before 1928 |
—
|
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: before 1928 | Statement: [Bashkir language, usedArabicAlphabet, before 1928]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedArabicAlphabet Context triple: [Bashkir language, usedArabicAlphabet, before 1928]
-
A.
usesAlphabet
chosen
Indicates that one entity employs or is written using the alphabet or writing system associated with another entity.
-
B.
hasNameInArabic
Indicates that an entity is associated with a specific name expressed in the Arabic language.
-
C.
hasContextualLetterForms
Indicates that the written form of a letter changes shape depending on its surrounding characters or position within a word.
-
D.
usesDiacritics
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
-
E.
usesAdditionalLettersFrom
Indicates that one entity forms or derives its representation by incorporating extra letters taken from another entity beyond those originally present.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8d9102c819090af78cae50f0ff2 |
completed | March 1, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69a4b731e25c8190b5ea8466648c2c9a |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.