Triple
T15610553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julia Hamer |
E375277
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Norwich, England |
E41722
|
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: Norwich, England | Statement: [Julia Hamer, residence, Norwich, England]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norwich, England Context triple: [Julia Hamer, residence, Norwich, England]
-
A.
Norfolk, England
Norfolk, England is a largely rural county in East Anglia known for its flat landscapes, the Norfolk Broads waterways, and the historic city of Norwich.
-
B.
Norwich
chosen
Norwich is a historic cathedral city in Norfolk, England, known for its medieval architecture and role as a regional cultural and economic center.
-
C.
Norwich
Norwich is a rural township in Oxford County, Ontario, known for its agricultural community and small-town character.
-
D.
Suffolk, England
Suffolk, England is a historic rural county in East Anglia known for its medieval towns, coastal landscapes, and agricultural heritage.
-
E.
Durham, England
Durham, England is a historic cathedral city in northeast England known for its Norman architecture, including Durham Cathedral and Castle, and as a prominent university center.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e8024948190a6c711f2e5c2aac4 |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56d76c108190aa3cae2d7e17c301 |
completed | May 9, 2026, 3:46 p.m. |
Created at: April 10, 2026, 4:13 a.m.