Triple
T8713444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wasserburg am Inn |
E206835
|
entity |
| Predicate | distanceToMunich |
P84034
|
FINISHED |
| Object | approximately 50 kilometres |
—
|
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 50 kilometres | Statement: [Wasserburg am Inn, distanceToMunich, approximately 50 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMunich Context triple: [Wasserburg am Inn, distanceToMunich, approximately 50 kilometres]
-
A.
distanceToBerlin
Indicates the spatial distance between a given entity’s location and the city of Berlin.
-
B.
distanceToRosenheim
Indicates the spatial distance between a given entity and the location Rosenheim.
-
C.
distanceToStuttgart
Indicates the measured distance between a given entity’s location and the city of Stuttgart.
-
D.
distanceToNuremberg
Indicates the spatial distance between a given entity and the location of Nuremberg.
-
E.
distanceToLeipzig
Indicates the spatial distance between a given entity’s location and the city of Leipzig.
- 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5cd522a88190a32facd86206af66 |
completed | March 31, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69cc456e806c819087e7d66ee737f242 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc46c40c54819093d174a4203f9515 |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:35 p.m.