Triple
T1999977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reading railway station |
E43445
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Basingstoke |
E105229
|
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: Basingstoke | Statement: [Reading railway station, connectsTo, Basingstoke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Basingstoke Context triple: [Reading railway station, connectsTo, Basingstoke]
-
A.
Basingstoke
chosen
Basingstoke is a large town in Hampshire, England, known as a major commercial and retail centre with significant modern development and transport links.
-
B.
Wokingham
Wokingham is a historic market town in Berkshire, England, known for its traditional town center and role as a commuter hub for nearby Reading and London.
-
C.
Farnham
Farnham is a historic market town in southern England known for its Georgian streets, medieval castle, and surrounding Surrey countryside.
-
D.
Bracknell
Bracknell is a town in the English county of Berkshire, known as a post-war New Town and commercial centre in the Thames Valley.
-
E.
Slough
Slough is a large industrial and commercial town in southern England, known for its diverse population and proximity to London and Heathrow Airport.
- 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_69a88715dbbc8190b2299e29e955d997 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb87f78f0819098e787a5f3e062fd |
completed | March 7, 2026, 5:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1f84148a08190a514fb15d550a550 |
completed | March 11, 2026, 11:18 p.m. |
Created at: March 4, 2026, 7:37 p.m.