Triple
T12528823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unkel |
E299505
|
entity |
| Predicate | hasRiverKilometre |
P56863
|
FINISHED |
| Object | Rhine kilometre approximately 640 |
—
|
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: Rhine kilometre approximately 640 | Statement: [Unkel, hasRiverKilometre, Rhine kilometre approximately 640]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiverKilometre Context triple: [Unkel, hasRiverKilometre, Rhine kilometre approximately 640]
-
A.
waterwayLengthKilometres
Indicates the total length of a waterway, measured in kilometres.
-
B.
riverKilometerContext
chosen
Indicates the position or context of something along a river, measured in river kilometers from a defined reference point.
-
C.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
D.
hasApproxLengthAlongRiver
Indicates that an entity has an approximate measured length that follows the course of a river rather than a straight-line distance.
-
E.
hasLongestRiver
Indicates that one entity possesses or contains the river that is longer than any other river associated with the compared entities.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.