Triple
T15187831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spay |
E362922
|
entity |
| Predicate | hasTransportConnection |
P845
|
FINISHED |
| Object | Bundesstraße 9 |
E742804
|
NE 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: Bundesstraße 9 | Statement: [Spay, hasTransportConnection, Bundesstraße 9]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bundesstraße 9 Context triple: [Spay, hasTransportConnection, Bundesstraße 9]
-
A.
Bundesstraße 9
chosen
Bundesstraße 9 is a major German federal highway running along the western part of the country, connecting numerous cities and towns near the Rhine.
-
B.
Bundesstraße 96
Bundesstraße 96 is a major German federal highway running in a north–south direction, notably connecting Berlin with the Baltic Sea island of Rügen.
-
C.
Bundesstraße 91
Bundesstraße 91 is a German federal highway in the state of Saxony-Anhalt that connects the town of Weißenfels with other regional centers.
-
D.
Bundesstraße 7
Bundesstraße 7 is a major German federal highway running east–west across several states and connecting numerous cities and regions.
-
E.
Bundesstraße 8
Bundesstraße 8 is a major German federal highway running east–west through several states and connecting numerous towns and cities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0067995fc8190b048f15086bd42f0 |
completed | April 15, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec895b59c81908a09f8393a35aa13 |
completed | May 9, 2026, 5:39 a.m. |
Created at: April 10, 2026, 3:09 a.m.