Triple
T19888780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Budapest |
E477973
|
entity |
| Predicate | hasRouteSegment |
P18687
|
FINISHED |
| Object | Paris–Strasbourg |
—
|
NE NERFINISHED |
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: Paris–Strasbourg | Statement: [Paris–Budapest, hasRouteSegment, Paris–Strasbourg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paris–Strasbourg Context triple: [Paris–Budapest, hasRouteSegment, Paris–Strasbourg]
-
A.
Paris–Strasbourg
chosen
Paris–Strasbourg is a major high-speed rail corridor in France linking the capital with the Alsatian city near the German border.
-
B.
Paris–Marseille
Paris–Marseille is a major French intercity rail corridor linking the capital Paris with the Mediterranean port city of Marseille.
-
C.
Cologne–Paris
Cologne–Paris is a former low-cost international air route connecting the German city of Cologne with the French capital, Paris.
-
D.
Paris–Luxembourg
Paris–Luxembourg is a major international railway route linking the French capital Paris with the Grand Duchy of Luxembourg.
-
E.
Paris–Mulhouse route
The Paris–Mulhouse route is a major French transport corridor linking the capital Paris with the eastern city of Mulhouse, serving as an important axis for regional and international traffic.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6590c1b9c8190abbfaa04b80713b3 |
completed | April 20, 2026, 4:49 p.m. |
Created at: April 10, 2026, 1:52 p.m.