Triple
T34888511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montreal–Quebec City |
E1006216
|
entity |
| Predicate | hasRailTerminusCity |
P21210
|
FINISHED |
| Object | Montreal |
—
|
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: Montreal | Statement: [Montreal–Quebec City, hasRailTerminusCity, Montreal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailTerminusCity Context triple: [Montreal–Quebec City, hasRailTerminusCity, Montreal]
-
A.
railroadTerminusFor
chosen
Indicates that one location serves as the end point or final station of a particular railroad line for another location.
-
B.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
C.
railwayTerminalServed
Indicates that a railway terminal is served by, or has service connections with, a particular railway line, route, or operator.
-
D.
terminusCityIsPort
Indicates that the city where a route or journey ends functions as a port.
-
E.
isCapitalCityStationOf
Indicates that a particular station serves as the main or primary railway/transport station of a capital city.
- F. None of above.
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_69f76dbedb288190afe5780710847410 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd44474ed48190ac372e4c88d762ed |
completed | May 8, 2026, 2:02 a.m. |
| PD | Predicate disambiguation | batch_69fd41ef28a48190a66959be5c964461 |
completed | May 8, 2026, 1:52 a.m. |
Created at: May 3, 2026, 4 p.m.