Triple
T1908789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hertfordshire |
E38060
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Ashwell
Ashwell is a historic village and civil parish in the county of Hertfordshire, England, known for its medieval architecture and picturesque rural setting.
|
E211882
|
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: Ashwell | Statement: [Hertfordshire, containsSettlement, Ashwell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashwell Context triple: [Hertfordshire, containsSettlement, Ashwell]
-
A.
Berkhamsted
Berkhamsted is a historic market town in Hertfordshire, England, known for its medieval castle remains and role as a commuter hub northwest of London.
-
B.
Wantage
Wantage is a historic market town in Oxfordshire, England, best known as the birthplace of King Alfred the Great.
-
C.
Bracknell
Bracknell is a town in the English county of Berkshire, known as a post-war New Town and commercial centre in the Thames Valley.
-
D.
Esher
Esher is a suburban town in the borough of Elmbridge in Surrey, England, known for its affluent residential character and proximity to London.
-
E.
Slough
Slough is a large industrial and commercial town in southern England, known for its diverse population and proximity to London and Heathrow Airport.
- 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: Ashwell Triple: [Hertfordshire, containsSettlement, Ashwell]
Generated description
Ashwell is a historic village and civil parish in the county of Hertfordshire, England, known for its medieval architecture and picturesque rural setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ashwell Target entity description: Ashwell is a historic village and civil parish in the county of Hertfordshire, England, known for its medieval architecture and picturesque rural setting.
-
A.
Berkhamsted
Berkhamsted is a historic market town in Hertfordshire, England, known for its medieval castle remains and role as a commuter hub northwest of London.
-
B.
Wantage
Wantage is a historic market town in Oxfordshire, England, best known as the birthplace of King Alfred the Great.
-
C.
Bracknell
Bracknell is a town in the English county of Berkshire, known as a post-war New Town and commercial centre in the Thames Valley.
-
D.
Esher
Esher is a suburban town in the borough of Elmbridge in Surrey, England, known for its affluent residential character and proximity to London.
-
E.
Slough
Slough is a large industrial and commercial town in southern England, known for its diverse population and proximity to London and Heathrow Airport.
- 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_69a8862a26088190aae5243695aeefc0 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb1b55edc8190bce8ac97196939a9 |
completed | March 7, 2026, 5:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeafdad3c8190be7aeaed8bdeac43 |
completed | March 8, 2026, 9:32 p.m. |
| NEDg | Description generation | batch_69adeb7075f48190a27b5039c3b4691e |
completed | March 8, 2026, 9:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adec37a4f88190961edf8f9c81773c |
completed | March 8, 2026, 9:37 p.m. |
Created at: March 4, 2026, 7:35 p.m.