Triple
T6812465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armenian language |
E156667
|
entity |
| Predicate | historicalNumberOfLettersInAlphabet |
P73223
|
FINISHED |
| Object | 36 |
—
|
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: 36 | Statement: [Armenian language, historicalNumberOfLettersInAlphabet, 36]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalNumberOfLettersInAlphabet Context triple: [Armenian language, historicalNumberOfLettersInAlphabet, 36]
-
A.
alphabetSizeLatin
Indicates the number of distinct letters in the Latin alphabet used in a given context or system.
-
B.
hasApproximateNumberOfLetters
Indicates that an entity is associated with a number that roughly, but not exactly, corresponds to the count of letters it contains.
-
C.
usesLatinAlphabetSince
Indicates that an entity has employed the Latin alphabet as its writing system starting from a specific point in time and continuing thereafter.
-
D.
writingSystemHistorically
Indicates that one writing system was historically used for, associated with, or served as a predecessor to another writing system.
-
E.
alphabet
Indicates that one entity is an alphabet or set of symbols used for representing elements (such as characters or tokens) in relation to another entity.
- F. None of above. chosen
Provenance (4 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d329861881909f65bd1017ea384b |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09bb4f881909bf20c188cb3e8e1 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d1d5f1908190989efc8a2d18c965 |
completed | March 27, 2026, 6:52 p.m. |
Created at: March 27, 2026, 2:17 p.m.