Triple

T403603
Position Surface form Disambiguated ID Type / Status
Subject Edward I of England E9336 entity
Predicate placeOfDeath P21 FINISHED
Object Cumberland
Cumberland is a historic county in northwestern England, bordering Scotland and encompassing part of the Lake District.
E53833 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: Cumberland | Statement: [Edward I of England, placeOfDeath, Cumberland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cumberland
Context triple: [Edward I of England, placeOfDeath, Cumberland]
  • A. Calvert
    Calvert is a given name most notably borne by Calvert Vaux, the 19th-century British-American architect and landscape designer who co-designed New York City's Central Park.
  • B. Brunswick
    Brunswick is a historic city in northern Germany known for its medieval heritage and as the birthplace of mathematician Carl Friedrich Gauss.
  • C. Monmouth
    Monmouth is a historic market town in Monmouthshire, Wales, known for its medieval architecture and position near the English border.
  • D. Piedmont
    Piedmont is a historically significant region in northwestern Italy, known for its role in the unification of Italy and for its rich wine, culinary, and alpine traditions.
  • E. Brewster
    Brewster is a coastal town on Cape Cod in Massachusetts known for its scenic beaches, historic charm, and bayside conservation lands.
  • 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: Cumberland
Triple: [Edward I of England, placeOfDeath, Cumberland]
Generated description
Cumberland is a historic county in northwestern England, bordering Scotland and encompassing part of the Lake District.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Cumberland
Target entity description: Cumberland is a historic county in northwestern England, bordering Scotland and encompassing part of the Lake District.
  • A. Calvert
    Calvert is a given name most notably borne by Calvert Vaux, the 19th-century British-American architect and landscape designer who co-designed New York City's Central Park.
  • B. Brunswick
    Brunswick is a historic city in northern Germany known for its medieval heritage and as the birthplace of mathematician Carl Friedrich Gauss.
  • C. Monmouth
    Monmouth is a historic market town in Monmouthshire, Wales, known for its medieval architecture and position near the English border.
  • D. Piedmont
    Piedmont is a historically significant region in northwestern Italy, known for its role in the unification of Italy and for its rich wine, culinary, and alpine traditions.
  • E. Brewster
    Brewster is a coastal town on Cape Cod in Massachusetts known for its scenic beaches, historic charm, and bayside conservation lands.
  • 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_69a2e8004cb88190b92ed1add6abf41a completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2eca226fc81909d6ccc38a637daa6 completed Feb. 28, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a42a12e5548190aedc6e18ef24c0ce completed March 1, 2026, 11:59 a.m.
NEDg Description generation batch_69a42dcefe4c8190a2ca6d5bc501c3b8 completed March 1, 2026, 12:15 p.m.
NED2 Entity disambiguation (via description) batch_69a42e24eca08190ad47f69d8d0743d0 completed March 1, 2026, 12:16 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.