Triple
T2801471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suffolk, England |
E53163
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Sudbury
Sudbury is a historic market town in Suffolk, England, known for its medieval architecture and association with painter Thomas Gainsborough.
|
E299682
|
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: Sudbury | Statement: [Suffolk, England, containsSettlement, Sudbury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sudbury Context triple: [Suffolk, England, containsSettlement, Sudbury]
-
A.
Sudbury
Sudbury is a major city in northern Ontario, Canada, known for its mining industry and numerous surrounding lakes.
-
B.
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.
-
C.
Fitchburg
Fitchburg is a small city in north-central Massachusetts known for its industrial history, hilly terrain, and role as a regional rail hub.
-
D.
Haverhill
Haverhill is a historic city in northeastern Massachusetts that functions as a suburban community within the Greater Boston metropolitan area.
-
E.
Andover
Andover is a town in Hampshire, England, known in part for its role as a major administrative and logistical center for the British Army.
- 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: Sudbury Triple: [Suffolk, England, containsSettlement, Sudbury]
Generated description
Sudbury is a historic market town in Suffolk, England, known for its medieval architecture and association with painter Thomas Gainsborough.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sudbury Target entity description: Sudbury is a historic market town in Suffolk, England, known for its medieval architecture and association with painter Thomas Gainsborough.
-
A.
Sudbury
Sudbury is a major city in northern Ontario, Canada, known for its mining industry and numerous surrounding lakes.
-
B.
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.
-
C.
Fitchburg
Fitchburg is a small city in north-central Massachusetts known for its industrial history, hilly terrain, and role as a regional rail hub.
-
D.
Haverhill
Haverhill is a historic city in northeastern Massachusetts that functions as a suburban community within the Greater Boston metropolitan area.
-
E.
Andover
Andover is a town in Hampshire, England, known in part for its role as a major administrative and logistical center for the British Army.
- 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_69ab495a90788190941b6917e1eca3a6 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abde1117148190b0c98f906f1c872e |
completed | March 7, 2026, 8:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc66d1e488190a4b85decfb38097f |
completed | March 10, 2026, 7:21 a.m. |
| NEDg | Description generation | batch_69afc8b12b848190ad514eed2d26a90f |
completed | March 10, 2026, 7:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afc9413e1881908fc091b98913e1cf |
completed | March 10, 2026, 7:33 a.m. |
Created at: March 6, 2026, 9:58 p.m.