Triple
T16847271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lužnice River |
E409576
|
entity |
| Predicate | lengthInCzechRepublic |
P125089
|
FINISHED |
| Object | approximately 157 km |
—
|
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 157 km | Statement: [Lužnice River, lengthInCzechRepublic, approximately 157 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lengthInCzechRepublic Context triple: [Lužnice River, lengthInCzechRepublic, approximately 157 km]
-
A.
lengthInSlovakia
Indicates the extent or distance of something measured specifically within the territory of Slovakia.
-
B.
lengthInPoland
Indicates that the specified length measurement is taken within the context or territory of Poland.
-
C.
rankByLengthInSlovakia
Indicates that entities are ordered or compared based on their length within the context of Slovakia.
-
D.
lengthInGermany
Indicates the extent or duration of something measured specifically within the geographic or jurisdictional boundaries of Germany.
-
E.
lengthInHungary
Indicates that something has a specified length measured within the context or territory of Hungary.
- 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b354eaf081908fe6f84a330d7866 |
completed | April 18, 2026, 4:37 p.m. |
| PD | Predicate disambiguation | batch_69e32b87b4248190aaddb05e88452356 |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:24 a.m.