Triple
T14169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blitz |
E283
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object |
Coventry
Coventry is a historic city in England, best known for its medieval cathedral destroyed in World War II and its symbolic postwar reconciliation efforts.
|
E14847
|
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: Coventry | Statement: [Blitz, location, Coventry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coventry Context triple: [Blitz, location, Coventry]
-
A.
Gloucester
Gloucester is a historic coastal city in northeastern Massachusetts known for its long-standing fishing industry and maritime heritage.
-
B.
Birmingham
Birmingham is a major industrial city in England’s West Midlands, historically significant for its manufacturing heritage and heavy bombing during the Second World War.
-
C.
Surrey
Surrey is a county in southeast England known for its historic towns, affluent suburbs, and proximity to London.
-
D.
Stockport
Stockport is a large town in Greater Manchester, England, situated southeast of central Manchester and forming part of the wider Manchester urban area.
-
E.
Leigh
Leigh is a given name and surname of English origin, used for all genders and often considered a variant spelling of "Lee."
- 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: Coventry Triple: [Blitz, location, Coventry]
Generated description
Coventry is a historic city in England, best known for its medieval cathedral destroyed in World War II and its symbolic postwar reconciliation efforts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Coventry Target entity description: Coventry is a historic city in England, best known for its medieval cathedral destroyed in World War II and its symbolic postwar reconciliation efforts.
-
A.
Gloucester
Gloucester is a historic coastal city in northeastern Massachusetts known for its long-standing fishing industry and maritime heritage.
-
B.
Birmingham
Birmingham is a major industrial city in England’s West Midlands, historically significant for its manufacturing heritage and heavy bombing during the Second World War.
-
C.
Surrey
Surrey is a county in southeast England known for its historic towns, affluent suburbs, and proximity to London.
-
D.
Warrington
Warrington is a large town in Cheshire, England, situated between Liverpool and Manchester on the River Mersey and known historically for its role in industry and transport.
-
E.
Stockport
Stockport is a large town in Greater Manchester, England, situated southeast of central Manchester and forming part of the wider Manchester urban area.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a240014418819090625e2fb774a2e6 |
completed | Feb. 28, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2a3cd69288190b2321a4478699c56 |
completed | Feb. 28, 2026, 8:14 a.m. |
| NEDg | Description generation | batch_69a2a5e6e260819085b4de29c3234b54 |
completed | Feb. 28, 2026, 8:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2a65e32e881908e743380f8868cc0 |
completed | Feb. 28, 2026, 8:25 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.