Triple
T7921841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yellowhead Highway |
E183961
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Jasper |
E401195
|
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: Jasper | Statement: [Yellowhead Highway, passesThrough, Jasper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jasper Context triple: [Yellowhead Highway, passesThrough, Jasper]
-
A.
Jasper
Jasper is a cloud-based Internet of Things (IoT) platform company that provides tools for managing and monetizing connected devices and services.
-
B.
Jasper
Jasper is a powerful and antagonistic Gem warrior in the animated series "Steven Universe," known for her brute strength, loyalty to Homeworld, and complex rivalry with the Crystal Gems.
-
C.
Jasper
Jasper is a small city in northwestern Alabama known historically for its coal mining and role in the state's industrial development.
-
D.
Jasper
Jasper is one of Cruella de Vil’s bumbling henchmen who helps steal Dalmatian puppies in Disney’s "One Hundred and One Dalmatians."
-
E.
Jasper
chosen
Jasper is a small resort town in Alberta, Canada, serving as a gateway and service hub for visitors to the surrounding Rocky Mountains and Jasper National Park.
- 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_69ca828efbe48190bd48482650182e79 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a9499cc8190b6bd81f4625c77ab |
completed | March 31, 2026, 3:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5beea7988190972f7d02881d98f6 |
completed | March 31, 2026, 5:30 a.m. |
Created at: March 30, 2026, 5:06 p.m.