Triple
T629645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Midlands |
E15896
|
entity |
| Predicate | hasCounty |
P285
|
FINISHED |
| Object |
Rutland
Rutland is a small historic county in the East Midlands of England, known for its rural character and Rutland Water reservoir.
|
E86840
|
NE FINISHED |
How this triple was built (4 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: Rutland | Statement: [East Midlands, hasCounty, Rutland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rutland Context triple: [East Midlands, hasCounty, Rutland]
-
A.
Rutland
Rutland is a small city in central Vermont known historically as a marble quarrying center and as a regional hub for commerce and outdoor recreation.
-
B.
Berkshire
Berkshire is a historic county in South East England known for its royal connections, including Windsor Castle, and its mix of affluent towns and rural landscapes.
-
C.
Suffolk
Suffolk is a historic rural county in eastern England known for its coastal towns, medieval villages, and agricultural landscapes.
-
D.
Cumberland
Cumberland is a historic county in northwestern England, bordering Scotland and encompassing part of the Lake District.
-
E.
Hampshire
Hampshire is a county on England’s south coast known for its historic cities, naval and military heritage, and mix of rural countryside and coastal areas.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rutland Triple: [East Midlands, hasCounty, Rutland]
Generated description
Rutland is a small historic county in the East Midlands of England, known for its rural character and Rutland Water reservoir.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rutland Target entity description: Rutland is a small historic county in the East Midlands of England, known for its rural character and Rutland Water reservoir.
-
A.
Rutland
Rutland is a small city in central Vermont known historically as a marble quarrying center and as a regional hub for commerce and outdoor recreation.
-
B.
Berkshire
Berkshire is a historic county in South East England known for its royal connections, including Windsor Castle, and its mix of affluent towns and rural landscapes.
-
C.
Suffolk
Suffolk is a historic rural county in eastern England known for its coastal towns, medieval villages, and agricultural landscapes.
-
D.
Cumberland
Cumberland is a historic county in northwestern England, bordering Scotland and encompassing part of the Lake District.
-
E.
Hampshire
Hampshire is a county on England’s south coast known for its historic cities, naval and military heritage, and mix of rural countryside and coastal areas.
- F. None of above. chosen
Provenance (5 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ec051bc8190b3e3f8651a367d77 |
completed | March 1, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a63742d8a8819087c7c2fa2430da75 |
completed | March 3, 2026, 1:20 a.m. |
| NEDg | Description generation | batch_69a637ef099c8190a23f59a39e4e110a |
completed | March 3, 2026, 1:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a63c075f988190aa9f7073b44fb97b |
completed | March 3, 2026, 1:40 a.m. |
Created at: March 1, 2026, 7:35 p.m.