Triple
T31421288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bundesstraße |
E801534
|
entity |
| Predicate | parallelClass |
P172231
|
FINISHED |
| Object | Autobahn |
—
|
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: Autobahn | Statement: [Bundesstraße, parallelClass, Autobahn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parallelClass Context triple: [Bundesstraße, parallelClass, Autobahn]
-
A.
parallelType
Indicates that one entity runs in parallel to another, specifying the type or manner of their parallel relationship.
-
B.
parallel
Indicates that two or more entities maintain a constant separation and direction without intersecting or converging.
-
C.
parallelUnit
Indicates that two or more units operate or are arranged in parallel, functioning simultaneously and independently within the same context.
-
D.
parallelSeeTo
Indicates that one entity observes or attends to another entity in a manner that is simultaneous or coordinated with a comparable act of seeing by a different entity.
-
E.
parallelPosition
Indicates that two entities occupy positions that are aligned in parallel relative to a reference frame or axis.
- 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_69f348c26f048190b4adadd71b4596c5 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a9603b208190b3533ea2b441514c |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a7548eb48190a69b60a3c6ad53b9 |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a915ead881909463ae46419c343e |
completed | May 3, 2026, 1:47 a.m. |
Created at: April 30, 2026, 8:48 p.m.