Triple
T10306165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A9 motorway (Germany) |
E241766
|
entity |
| Predicate | routeNumber |
P1864
|
FINISHED |
| Object | A9 |
E97820
|
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: A9 | Statement: [A9 motorway (Germany), routeNumber, A9]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A9 Context triple: [A9 motorway (Germany), routeNumber, A9]
-
A.
A9
A9 is a major Swiss motorway that runs across the southwestern part of the country, connecting key regions in Valais and linking to international routes.
-
B.
A9
chosen
A9 is a major German autobahn that runs north–south, connecting Berlin with Munich and passing through regions such as Middle Franconia.
-
C.
A90
A90 is the orbital motorway encircling Rome, Italy, serving as a major ring road for traffic around the city.
-
D.
A91
A91 is a major Italian motorway connecting Rome to Leonardo da Vinci–Fiumicino Airport.
-
E.
A96
A96 is a major German autobahn in southern Bavaria that connects Munich with Lindau near the Austrian and Swiss borders.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d30a6c888190acdd0a645247736a |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d60be1481909dc1330f150e3897 |
completed | April 9, 2026, 3:30 a.m. |
Created at: April 6, 2026, 11:46 a.m.