Triple
T11517758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eramosa River |
E273074
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Guelph |
E34046
|
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: Guelph | Statement: [Eramosa River, hasNearbySettlement, Guelph]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guelph Context triple: [Eramosa River, hasNearbySettlement, Guelph]
-
A.
Guelph
chosen
Guelph is a mid-sized Canadian city known for its strong manufacturing base, historic architecture, and the University of Guelph.
-
B.
Brantford
Brantford is a city in southwestern Ontario, Canada, known as the hometown of hockey legend Wayne Gretzky and for its historic role in the development of telephone technology.
-
C.
Oshawa
Oshawa is a city in southern Ontario, Canada, known historically as a major automotive manufacturing center and part of the Greater Toronto Area.
-
D.
Waterloo, Ontario
Waterloo, Ontario is a Canadian city in the Regional Municipality of Waterloo best known as a major tech and innovation hub and home to the University of Waterloo and Wilfrid Laurier University.
-
E.
St. Catharines
St. Catharines is a city in southern Ontario, Canada, known for its location near Niagara Falls and its role as a regional commercial and manufacturing center.
- 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fcc72a48190b81acedfcc8685d3 |
completed | April 10, 2026, 4:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68e99c2608190b923ca8a9178fea2 |
completed | May 2, 2026, 11:54 p.m. |
Created at: April 8, 2026, 9:36 p.m.