Triple
T3251505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Met Office |
E68189
|
entity |
| Predicate | previousHeadquartersLocation |
P62
|
FINISHED |
| Object | Bracknell |
E58983
|
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: Bracknell | Statement: [Met Office, previousHeadquartersLocation, Bracknell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bracknell Context triple: [Met Office, previousHeadquartersLocation, Bracknell]
-
A.
Bracknell
chosen
Bracknell is a town in the English county of Berkshire, known as a post-war New Town and commercial centre in the Thames Valley.
-
B.
Bracknell Forest
Bracknell Forest is a unitary authority area and borough in Berkshire, South East England, encompassing the town of Bracknell and surrounding communities.
-
C.
Slough
Slough is a large industrial and commercial town in southern England, known for its diverse population and proximity to London and Heathrow Airport.
-
D.
Aylesbury
Aylesbury is a historic market town in southern England that serves as an important commercial and administrative center in Buckinghamshire.
-
E.
Beaconsfield
Beaconsfield is a suburban city on the western part of the Island of Montreal in Quebec, Canada, known for its residential character and waterfront along Lake Saint-Louis.
- 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_69ad858e4c708190aa31d486cfee8a6a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf425394819084ae6304da211c00 |
completed | March 8, 2026, 5:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b67b99c00481908b846c610bd29993 |
completed | March 15, 2026, 9:27 a.m. |
Created at: March 8, 2026, 3:09 p.m.