Triple
T22732213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leamington Spa railway station |
E562163
|
entity |
| Predicate | hasServiceTo |
P6787
|
FINISHED |
| Object | Bournemouth |
—
|
NE NERFINISHED |
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: Bournemouth | Statement: [Leamington Spa railway station, hasServiceTo, Bournemouth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bournemouth Context triple: [Leamington Spa railway station, hasServiceTo, Bournemouth]
-
A.
Bournemouth
chosen
Bournemouth is a large coastal resort town on England’s south coast, known for its sandy beaches, tourism, and role as a regional commercial and transport hub.
-
B.
Poole
Poole is a coastal town and seaport in Dorset, England, known for its large natural harbour and maritime activities.
-
C.
Bristol
Bristol is a city in central Connecticut known for being the home of ESPN and for its historic clock-making industry.
-
D.
Bristol
Bristol is a city in central Connecticut known historically for its clock-making industry and as the longtime home of ESPN’s headquarters.
-
E.
Bristol
Bristol is a small town located in Dane County in the U.S. state of Wisconsin.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24550859c81908727d91efc3a81b4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1792ef5bc819088af71bdc96ed41b |
completed | April 29, 2026, 3:21 a.m. |
Created at: April 17, 2026, 3:21 p.m.