Triple
T9813651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saar River |
E238341
|
entity |
| Predicate | lengthInGermany |
P90150
|
FINISHED |
| Object | approximately 120 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 120 km | Statement: [Saar River, lengthInGermany, approximately 120 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lengthInGermany Context triple: [Saar River, lengthInGermany, approximately 120 km]
-
A.
lengthInPoland
Indicates that the specified length measurement is taken within the context or territory of Poland.
-
B.
lengthInKm
Indicates that one entity specifies the length or distance of another entity measured in kilometers.
-
C.
trackLengthApproxKm
Indicates that one entity has an approximate track length, measured in kilometers, associated with it.
-
D.
lengthInHungary
Indicates that something has a specified length measured within the context or territory of Hungary.
-
E.
locatedInPartOfGermany
Indicates that one entity is geographically situated within a specific region or part of Germany.
- 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_69ca84defac48190abc1148804f184c1 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb22410208190b82b81a4df800f80 |
completed | April 2, 2026, 12:02 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
| PDg | Predicate description generation | batch_69cd06abc9248190a506b64e9c516d03 |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:30 p.m.