Triple
T669149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Sea flood of 1953 |
E12932
|
entity |
| Predicate | worstAffectedRegion |
P1586
|
FINISHED |
| Object | Essex |
E30848
|
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: Essex | Statement: [North Sea flood of 1953, worstAffectedRegion, Essex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Essex Context triple: [North Sea flood of 1953, worstAffectedRegion, Essex]
-
A.
Essex
chosen
Essex is a county in the east of England, known for its mix of rural landscapes, historic towns, and proximity to London.
-
B.
Suffolk
Suffolk is a historic rural county in eastern England known for its coastal towns, medieval villages, and agricultural landscapes.
-
C.
Sussex
Sussex is a traditional British dual-purpose chicken breed valued for both its meat and egg production.
-
D.
Hertfordshire
Hertfordshire is a county in southern England known for its historic market towns, countryside, and proximity to London.
-
E.
Hampshire
Hampshire is a county on England’s south coast known for its historic cities, naval and military heritage, and mix of rural countryside and coastal areas.
- 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a518e6348190b467c2fab3fd1f11 |
completed | March 1, 2026, 8:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeaad456481908cf9fb412bdf90f0 |
completed | March 8, 2026, 9:31 p.m. |
Created at: March 1, 2026, 7:36 p.m.