Triple
T456646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgian script |
E7247
|
entity |
| Predicate | hasUppercase |
P13694
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Georgian script, hasUppercase, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUppercase Context triple: [Georgian script, hasUppercase, no]
-
A.
hasUppercaseAndLowercase
Indicates that a string or text value contains at least one uppercase letter and at least one lowercase letter.
-
B.
hasLower
Indicates that one entity is positioned at a lower level, rank, or value relative to another entity.
-
C.
hasSpecialCharacter
Indicates that a given entity (such as a string or identifier) contains at least one non-alphanumeric special character.
-
D.
hasCase
Indicates that one entity is involved in, associated with, or characterized by a particular case, instance, or occurrence represented by another entity.
-
E.
hasAdditionalLetters
Indicates that one entity contains extra or more letters than another entity, beyond a specified base set or reference.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efa1616481909399f92551a0c9e3 |
completed | Feb. 28, 2026, 1:37 p.m. |
| PD | Predicate disambiguation | batch_69a2ede614b88190be07425f5535f56d |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2ee8b56d08190bd625626353d01b4 |
completed | Feb. 28, 2026, 1:32 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.