Triple
T15511684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastleigh railway station |
E368723
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Fareham |
E124893
|
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: Fareham | Statement: [Eastleigh railway station, connectsTo, Fareham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fareham Context triple: [Eastleigh railway station, connectsTo, Fareham]
-
A.
Fareham
chosen
Fareham is a market town in southern England situated between the cities of Southampton and Portsmouth.
-
B.
Havant
Havant is a market town and borough in south-east England, situated between Portsmouth and Chichester near the south coast.
-
C.
Fordingbridge
Fordingbridge is a small historic town on the River Avon in Hampshire, England, known for its medieval stone bridge and proximity to the New Forest.
-
D.
Folkestone
Folkestone is a coastal town and port in Kent, England, known as a gateway to continental Europe via the Channel Tunnel and nearby ferry links.
-
E.
Margate
Margate is a popular seaside resort town on South Africa’s KwaZulu-Natal coast, known for its beaches and holiday tourism.
- 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e04030c0208190a1931ea130075603 |
completed | April 16, 2026, 1:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6780ee3081908a0a833d887b1829 |
completed | May 9, 2026, 4:57 p.m. |
Created at: April 10, 2026, 3:56 a.m.