Triple
T4586557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bishop of Willesden |
E103380
|
entity |
| Predicate | locatedInEcclesiasticalProvince |
P3089
|
FINISHED |
| Object | Canterbury |
E72201
|
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: Canterbury | Statement: [Bishop of Willesden, locatedInEcclesiasticalProvince, Canterbury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Canterbury Context triple: [Bishop of Willesden, locatedInEcclesiasticalProvince, Canterbury]
-
A.
Canterbury
chosen
Canterbury is a historic cathedral city in Kent, England, renowned for its medieval architecture and status as a major center of Christian pilgrimage.
-
B.
Canterbury
Canterbury is a large region on New Zealand’s South Island, centered on the city of Christchurch and known for its expansive plains, alpine scenery, and diverse communities.
-
C.
Bristol
Bristol is a city in central Connecticut known for being the home of ESPN and for its historic clock-making industry.
-
D.
Bristol
Bristol is a city in central Connecticut known historically for its clock-making industry and as the longtime home of ESPN’s headquarters.
-
E.
Bristol
Bristol is a small town located in Dane County in the U.S. state of Wisconsin.
- 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_69bd43dccaf08190aa89e9991a289719 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5906a43c81908fb11bf8f94be122 |
completed | March 20, 2026, 2:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bde0b1b014819085543bd297f925c1 |
completed | March 21, 2026, 12:05 a.m. |
Created at: March 20, 2026, 1:10 p.m.