Triple
T12359299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wembley Central |
E294690
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | Sudbury |
E299682
|
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: Sudbury | Statement: [Wembley Central, formerName, Sudbury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sudbury Context triple: [Wembley Central, formerName, Sudbury]
-
A.
Sudbury
Sudbury is a small rural town in Rutland County, Vermont, known for its scenic landscapes and quiet, agricultural character.
-
B.
Sudbury
Sudbury is a major city in northern Ontario, Canada, known for its mining industry and numerous surrounding lakes.
-
C.
Sudbury
chosen
Sudbury is a historic market town in Suffolk, England, known for its medieval architecture and association with painter Thomas Gainsborough.
-
D.
Sudbury, Massachusetts
Sudbury, Massachusetts is a historic New England town west of Boston known for its colonial heritage, affluent residential character, and preserved rural landscapes.
-
E.
Fitchburg
Fitchburg is a small city in north-central Massachusetts known for its industrial history, hilly terrain, and role as a regional rail hub.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f90201481909359416b8b9f7871 |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f634721e948190bb8e97ef677b9f59 |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:54 p.m.