Triple
T36491732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omniglot |
E899066
|
entity |
| Predicate | numberOfCharactersPerAlphabet |
P58060
|
FINISHED |
| Object | approximately 20 to 40 |
—
|
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: approximately 20 to 40 | Statement: [Omniglot, numberOfCharactersPerAlphabet, approximately 20 to 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCharactersPerAlphabet Context triple: [Omniglot, numberOfCharactersPerAlphabet, approximately 20 to 40]
-
A.
alphabetSizeLatin
Indicates the number of distinct letters in the Latin alphabet used in a given context or system.
-
B.
numberOfCharacters
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
-
C.
alphabetSizeCondition
Indicates a constraint or requirement on the size of the alphabet used in a given context (e.g., a code, language, or symbol set).
-
D.
characterSetSize
chosen
Indicates the total number of distinct characters contained in or allowed by a given character set.
-
E.
numberOfCommonUseCharacters
Indicates the count of characters that are shared in common between two entities’ representations or strings.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:10 p.m.