Triple
T18456438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cessnock City |
E450912
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Kitchener
Kitchener is a small town in the Hunter Region of New South Wales, Australia, known for its coal mining heritage and rural character.
|
E1325028
|
NE FINISHED |
How this triple was built (4 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: Kitchener | Statement: [Cessnock City, contains, Kitchener]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kitchener Context triple: [Cessnock City, contains, Kitchener]
-
A.
Kitchener
Kitchener is a mid-sized city in southwestern Ontario, Canada, known for its manufacturing history and annual Oktoberfest celebration.
-
B.
Cobourg
Cobourg is a small town in Ontario, Canada, known for its historic downtown, sandy beach, and picturesque waterfront along Lake Ontario.
-
C.
Guelph
Guelph is a mid-sized Canadian city known for its strong manufacturing base, historic architecture, and the University of Guelph.
-
D.
Alliston
Alliston is a community in New Tecumseth, Ontario, Canada, known historically as the birthplace of insulin co-discoverer Sir Frederick Banting.
-
E.
Barrie
Barrie is a mid-sized city in central Ontario, Canada, located on the western shore of Lake Simcoe and known as a growing regional hub for commuters, industry, and recreation.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kitchener Triple: [Cessnock City, contains, Kitchener]
Generated description
Kitchener is a small town in the Hunter Region of New South Wales, Australia, known for its coal mining heritage and rural character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kitchener Target entity description: Kitchener is a small town in the Hunter Region of New South Wales, Australia, known for its coal mining heritage and rural character.
-
A.
Kitchener
Kitchener is a mid-sized city in southwestern Ontario, Canada, known for its manufacturing history and annual Oktoberfest celebration.
-
B.
Cobourg
Cobourg is a small town in Ontario, Canada, known for its historic downtown, sandy beach, and picturesque waterfront along Lake Ontario.
-
C.
Guelph
Guelph is a mid-sized Canadian city known for its strong manufacturing base, historic architecture, and the University of Guelph.
-
D.
Alliston
Alliston is a community in New Tecumseth, Ontario, Canada, known historically as the birthplace of insulin co-discoverer Sir Frederick Banting.
-
E.
Barrie
Barrie is a mid-sized city in central Ontario, Canada, located on the western shore of Lake Simcoe and known as a growing regional hub for commuters, industry, and recreation.
- F. None of above. chosen
Provenance (5 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5264ce5948190b57baa2ea71297a9 |
completed | April 19, 2026, 7 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a040fe7cb0481908266ee813d99cf87 |
completed | May 13, 2026, 5:45 a.m. |
| NEDg | Description generation | batch_6a04118472a08190b450dfe756475687 |
completed | May 13, 2026, 5:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0412b3f2288190a4090ae5363f7d9f |
completed | May 13, 2026, 5:57 a.m. |
Created at: April 10, 2026, 11:31 a.m.