Triple
T17400918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Pas, Manitoba |
E423082
|
entity |
| Predicate | hasRailFunction |
P112432
|
FINISHED |
| Object | junction for northern rail lines |
—
|
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: junction for northern rail lines | Statement: [The Pas, Manitoba, hasRailFunction, junction for northern rail lines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailFunction Context triple: [The Pas, Manitoba, hasRailFunction, junction for northern rail lines]
-
A.
hasRail
Indicates that something is equipped with, includes, or is connected to a rail or rail system.
-
B.
hasRailMode
Indicates that an entity is associated with or supports transportation via rail-based modes (such as trains, trams, or subways).
-
C.
hasRailConfiguration
Indicates that an entity is associated with, or characterized by, a particular arrangement or setup of rails.
-
D.
hasRailRoute
Indicates that there exists a rail-based transportation route or connection between the related entities.
-
E.
hasRailInterchangeFunction
chosen
Indicates that something serves as a location or facility where rail lines connect or intersect, allowing passengers or goods to transfer between them.
- 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_69d889d710288190bf0f4762801fefae |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43ac126788190b51323bde3c9ba69 |
completed | April 19, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69e3b02e6cc88190986e85e64ce9383e |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:45 a.m.