Triple
T30811799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waterloo County |
E784662
|
entity |
| Predicate | hadTransportationLink |
P94946
|
FINISHED |
| Object | Grand Trunk Railway |
—
|
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: Grand Trunk Railway | Statement: [Waterloo County, hadTransportationLink, Grand Trunk Railway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadTransportationLink Context triple: [Waterloo County, hadTransportationLink, Grand Trunk Railway]
-
A.
hasTransportationRelation
Indicates a relationship in which one entity provides, uses, is connected by, or is otherwise associated with a means or mode of transportation to another entity or location.
-
B.
hasGoodTransportLinks
Indicates that a place is well connected to other locations by efficient and convenient transport options.
-
C.
isTransportationLinkBetween
Indicates that there exists a transportation connection (such as a road, rail, air, or sea route) linking the two entities.
-
D.
hasTransportRoute
Indicates that there exists a designated transportation connection or route linking one entity to another.
-
E.
hadTransportRoutes
chosen
Indicates that there were established transportation routes or connections between the related entities.
- 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_69f224b4eda48190bd212ce4f3901e56 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6906564448190972c23b8344bc373 |
completed | May 3, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:43 p.m.