Triple
T25894368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Škurda River |
E652425
|
entity |
| Predicate | hasNameInCyrillicScript |
P34124
|
FINISHED |
| Object | Шкурда |
—
|
NE NERFINISHED |
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: Шкурда | Statement: [Škurda River, hasNameInCyrillicScript, Шкурда]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameInCyrillicScript Context triple: [Škurda River, hasNameInCyrillicScript, Шкурда]
-
A.
hasCyrillicAlphabetForm
chosen
Indicates that an entity has a corresponding representation or form written in the Cyrillic alphabet.
-
B.
hasNameInTeluguScript
Indicates that an entity is associated with a name written in the Telugu script.
-
C.
hasUnicodeName
Indicates that an entity is associated with a specific official Unicode name assigned to a character or symbol.
-
D.
hasUnicodeScript
Indicates that a character or text element belongs to a specific Unicode script category (such as Latin, Cyrillic, or Han).
-
E.
hasNameInSlavonic
Indicates that an entity has a specific name or designation expressed in a Slavonic language.
- 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_69e7ab3c6cc081908de59bfcc28ec19d |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 22, 2026, 8:22 a.m.