Triple
T31592196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A2 Süd Autobahn |
E806127
|
entity |
| Predicate | hasBurgenlandSection |
P181264
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [A2 Süd Autobahn, hasBurgenlandSection, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBurgenlandSection Context triple: [A2 Süd Autobahn, hasBurgenlandSection, yes]
-
A.
isInBundesland
Indicates that one entity (typically a place or city) is located within a specific German federal state (Bundesland).
-
B.
hasEuroregion
Indicates a relationship where a geographic or administrative entity is part of, or associated with, a specific Euroregion.
-
C.
hasCanton
Indicates that an entity is administratively divided into, or associated with, a specific canton.
-
D.
borderTownOnAustrianSide
Indicates that a town is located on the Austrian side of a border shared with another country.
-
E.
includesBelgianRegion
Indicates that one entity geographically or administratively contains or encompasses a region located in Belgium.
- 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_69f348d4891c8190b02bae3c8ecb68b7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
| PDg | Predicate description generation | batch_69f76759b3c48190ad8f1b33596f98c4 |
completed | May 3, 2026, 3:18 p.m. |
Created at: April 30, 2026, 10:28 p.m.