Triple
T1814723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haileybury College |
E40410
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Hertfordshire |
E60268
|
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: Hertfordshire | Statement: [Haileybury College, locatedIn, Hertfordshire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hertfordshire Context triple: [Haileybury College, locatedIn, Hertfordshire]
-
A.
Hertfordshire
chosen
Hertfordshire is a county in southern England known for its historic market towns, countryside, and proximity to London.
-
B.
Bedfordshire
Bedfordshire is a ceremonial and non-metropolitan county in the East of England, known for its mix of rural countryside, market towns, and the large town of Luton.
-
C.
Buckinghamshire
Buckinghamshire is a ceremonial and non-metropolitan county in South East England, known for its historic towns, Chiltern Hills countryside, and proximity to London.
-
D.
Northamptonshire
Northamptonshire is a historic, landlocked county in the East Midlands of England known for its market towns, rural landscapes, and long association with the footwear and leather industries.
-
E.
Essex
Essex is a county in the east of England, known for its mix of rural landscapes, historic towns, and proximity to London.
- 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_69a8864526c081908a3a4d74f689e2c5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa65f4628481909ca8e4c2302752ac |
completed | March 6, 2026, 5:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b53fc112688190be32ad336ebba91e |
completed | March 14, 2026, 11 a.m. |
Created at: March 4, 2026, 7:32 p.m.