Triple
T4046770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swiss motorway network |
E84083
|
entity |
| Predicate | hasRoute |
P4374
|
FINISHED |
| Object | A7 |
E228222
|
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: A7 | Statement: [Swiss motorway network, hasRoute, A7]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A7 Context triple: [Swiss motorway network, hasRoute, A7]
-
A.
A7
chosen
A7 is a major European motorway designation used for key north–south and east–west highway routes in several countries.
-
B.
A73
A73 is a major German autobahn in Bavaria and Thuringia that links cities such as Lichtenfels with the broader national motorway network.
-
C.
A8
A8 is a major numbered road designation used in several countries for important regional or intercity routes.
-
D.
A9
A9 is a major German autobahn that runs north–south, connecting Berlin with Munich and passing through regions such as Middle Franconia.
-
E.
A6
A6 is a major German autobahn that serves as an important east–west transport corridor in southern Germany.
- 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_69aed930bd5c819083e7dcc14fc44f69 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb62593c8190ab8462c4d9cd9d08 |
completed | March 9, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b55652228c8190a9f301676deb0055 |
completed | March 14, 2026, 12:36 p.m. |
Created at: March 9, 2026, 3:37 p.m.