Triple
T7990026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leicestershire |
E185975
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Coalville |
E305799
|
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: Coalville | Statement: [Leicestershire, contains, Coalville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coalville Context triple: [Leicestershire, contains, Coalville]
-
A.
Coalville
chosen
Coalville is an industrial town in Leicestershire, England, historically known for its coal mining and manufacturing heritage.
-
B.
Kineton
Kineton is a village in Warwickshire, England, known for its proximity to the historic Edgehill battlefield of the English Civil War.
-
C.
Wolverley
Wolverley is a village in Worcestershire, England, known as the birthplace of the renowned 18th-century printer and typographer John Baskerville.
-
D.
Deatsville
Deatsville is a small town in central Alabama known for its rural character and proximity to the Montgomery metropolitan area.
-
E.
Wrottesley
Wrottesley is an English surname historically associated with a prominent aristocratic family and the title Baron Wrottesley.
- 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_69ca829c6c308190ab05b43d234c52b2 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c4f98808190879113ad4af9bb4d |
completed | March 31, 2026, 3:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe0f5c22881908044a178d670684c |
completed | March 31, 2026, 2:57 p.m. |
Created at: March 30, 2026, 5:16 p.m.