Triple
T17800799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Litava River |
E444418
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Lítava |
—
|
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: Lítava | Statement: [Litava River, hasNameInLanguage, Lítava]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lítava Context triple: [Litava River, hasNameInLanguage, Lítava]
-
A.
Litava
chosen
Litava is a river known locally by this name, flowing through parts of Central Europe and contributing to the region’s natural landscape and waterways.
-
B.
Slaný
Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
-
C.
Karviná
Karviná is an industrial city in the Moravian-Silesian Region of the Czech Republic, historically part of Cieszyn Silesia and known for its coal mining heritage.
-
D.
Šamorín
Šamorín is a small town in southwestern Slovakia known for its equestrian sports complex, proximity to the Danube River, and growing role as a suburban area near Bratislava.
-
E.
Slaná
Slaná is a river in central Europe that flows through Slovakia and Hungary, where it is known as the Sajó.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e487ff42108190b82ceb4466aa2dff |
completed | April 19, 2026, 7:45 a.m. |
Created at: April 10, 2026, 10:13 a.m.