Triple
T3089647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suffolk |
E64456
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Kersey |
E299758
|
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: Kersey | Statement: [Suffolk, containsSettlement, Kersey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kersey Context triple: [Suffolk, containsSettlement, Kersey]
-
A.
Kersey
chosen
Kersey is a historic village in Suffolk, England, noted for its picturesque medieval buildings and traditional rural character.
-
B.
Buteshire
Buteshire is a historic county in western Scotland that encompassed the Isle of Bute and surrounding islands in the Firth of Clyde.
-
C.
Westland
Westland is a municipality in the Dutch province of South Holland known for its extensive greenhouse horticulture and flower production.
-
D.
Westland
Westland is a suburban city in southeastern Michigan, United States, known as part of the Detroit metropolitan area.
-
E.
Kessingland
Kessingland is a coastal village and civil parish in Suffolk, England, known for its long shingle beach and seaside tourism.
- 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_69ad857c97d88190b26f9b1c90839c77 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada20d8f788190b05b8b6b5042bc1a |
completed | March 8, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1f8a4c1f08190a80efd190e4ed07f |
completed | March 11, 2026, 11:20 p.m. |
Created at: March 8, 2026, 3:03 p.m.