Triple
T1434832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Liverpool Street |
E30536
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object |
Cheshunt
Cheshunt is a town in Hertfordshire, England, situated just north of London and known as a commuter hub with rail links into the capital.
|
E310201
|
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: Cheshunt | Statement: [London Liverpool Street, connectsTo, Cheshunt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cheshunt Context triple: [London Liverpool Street, connectsTo, Cheshunt]
-
A.
Waltham Cross
Waltham Cross is a town in southeastern England known for its historic Eleanor Cross and its location near the Greater London boundary.
-
B.
Teversham
Teversham is a small village and civil parish located near Cambridge in the South Cambridgeshire district of England.
-
C.
Chislehurst
Chislehurst is a suburban district in southeast London known for its historic commons, caves, and affluent residential character.
-
D.
Chigwell
Chigwell is a suburban town in the Epping Forest district of Essex, England, known for its affluent residential character and proximity to London.
-
E.
Harpenden
Harpenden is a commuter town in southern England known for its green spaces and affluent residential character.
- 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: Cheshunt Triple: [London Liverpool Street, connectsTo, Cheshunt]
Generated description
Cheshunt is a town in Hertfordshire, England, situated just north of London and known as a commuter hub with rail links into the capital.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cheshunt Target entity description: Cheshunt is a town in Hertfordshire, England, situated just north of London and known as a commuter hub with rail links into the capital.
-
A.
Waltham Cross
Waltham Cross is a town in southeastern England known for its historic Eleanor Cross and its location near the Greater London boundary.
-
B.
Teversham
Teversham is a small village and civil parish located near Cambridge in the South Cambridgeshire district of England.
-
C.
Chislehurst
Chislehurst is a suburban district in southeast London known for its historic commons, caves, and affluent residential character.
-
D.
Chigwell
Chigwell is a suburban town in the Epping Forest district of Essex, England, known for its affluent residential character and proximity to London.
-
E.
Harpenden
Harpenden is a commuter town in southern England known for its green spaces and affluent residential character.
- 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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c500a9888190a16fbb1ec97a79c9 |
completed | March 1, 2026, 11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b05570cd488190bd9ce6b3a854a427 |
completed | March 10, 2026, 5:31 p.m. |
| NEDg | Description generation | batch_69b061ddcc0c81908fa237d8c8aae72f |
completed | March 10, 2026, 6:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0628d5f608190b7a13ac2e8b8d721 |
completed | March 10, 2026, 6:27 p.m. |
Created at: March 1, 2026, 8 p.m.