Triple
T2048841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midland Main Line |
E45516
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Derby |
E53520
|
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: Derby | Statement: [Midland Main Line, connectsCity, Derby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Derby Context triple: [Midland Main Line, connectsCity, Derby]
-
A.
Derby
chosen
Derby is a historic city in Derbyshire, England, known for its industrial heritage, particularly in railways and engineering.
-
B.
Derby
Derby is a neighborhood within the Brazilian city of Recife, known for its central location and urban character.
-
C.
Derby City
Derby City is a popular nickname for Louisville, Kentucky, reflecting the city's fame as home of the Kentucky Derby horse race.
-
D.
Nottingham
Nottingham is a major city in the East Midlands of England, historically known for its lace-making and bicycle industries and famously associated with the legend of Robin Hood.
-
E.
Sheffield
Sheffield is a small rural town in southwestern Massachusetts known for its scenic landscapes, historic charm, and location in the Berkshires.
- 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_69a8891948208190ab7898da21824c77 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb98c70c48190beb98aad56d9daf1 |
completed | March 7, 2026, 5:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae652a87748190b9e18356ffb13bed |
completed | March 9, 2026, 6:14 a.m. |
Created at: March 4, 2026, 7:39 p.m.