Triple
T2570035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgian Supplement |
E57641
|
entity |
| Predicate | hasCharacterProperty |
P26444
|
FINISHED |
| Object | General_Category=Letter |
—
|
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: General_Category=Letter | Statement: [Georgian Supplement, hasCharacterProperty, General_Category=Letter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCharacterProperty Context triple: [Georgian Supplement, hasCharacterProperty, General_Category=Letter]
-
A.
haveProperty
Indicates that an entity possesses, exhibits, or is characterized by a particular property or attribute.
-
B.
hasSpecialCharacter
Indicates that a given entity (such as a string or identifier) contains at least one non-alphanumeric special character.
-
C.
hasUnicodeProperty
chosen
Indicates that an entity possesses a specific Unicode character property or set of properties (such as category, script, or other Unicode-defined attributes).
-
D.
hasParentCharacter
Indicates that one character is the parent of another character.
-
E.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd382928c8190b6316f3db48d8e73 |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.