Triple

T13081836
Position Surface form Disambiguated ID Type / Status
Subject Latymer Upper School E310225 entity
Predicate hasAlumni P51 FINISHED
Object Cressida Dick
Cressida Dick is a British senior police officer who served as the first female Commissioner of London's Metropolitan Police Service.
E1019654 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: Cressida Dick | Statement: [Latymer Upper School, hasAlumni, Cressida Dick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cressida Dick
Context triple: [Latymer Upper School, hasAlumni, Cressida Dick]
  • A. Stella Rimington
    Stella Rimington is a British intelligence officer and author best known for serving as the first female Director General of MI5.
  • B. Elizabeth Jeffreys
    Elizabeth Jeffreys was an 18th-century British noblewoman best known as the wife of Charles Pratt, 1st Earl Camden, a prominent jurist and politician.
  • C. Louise Shore
    Louise Shore is a television producer best known for her executive production work on the miniseries "A Teacher."
  • D. Jennifer Mordaunt
    Jennifer Mordaunt is a relative of British Conservative politician Penny Mordaunt.
  • E. Lynda La Plante
    Lynda La Plante is a British novelist, screenwriter, and former actress best known for her gritty crime dramas and influential work in television police procedurals.
  • 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: Cressida Dick
Triple: [Latymer Upper School, hasAlumni, Cressida Dick]
Generated description
Cressida Dick is a British senior police officer who served as the first female Commissioner of London's Metropolitan Police Service.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Cressida Dick
Target entity description: Cressida Dick is a British senior police officer who served as the first female Commissioner of London's Metropolitan Police Service.
  • A. Stella Rimington
    Stella Rimington is a British intelligence officer and author best known for serving as the first female Director General of MI5.
  • B. Elizabeth Jeffreys
    Elizabeth Jeffreys was an 18th-century British noblewoman best known as the wife of Charles Pratt, 1st Earl Camden, a prominent jurist and politician.
  • C. Louise Shore
    Louise Shore is a television producer best known for her executive production work on the miniseries "A Teacher."
  • D. Jennifer Mordaunt
    Jennifer Mordaunt is a relative of British Conservative politician Penny Mordaunt.
  • E. Lynda La Plante
    Lynda La Plante is a British novelist, screenwriter, and former actress best known for her gritty crime dramas and influential work in television police procedurals.
  • 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_69d806a733548190989cfd4ce981ca33 completed April 9, 2026, 8:05 p.m.
NER Named-entity recognition batch_69d9811add9881908a92186dab5b6d48 completed April 10, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d60e7b48819087e4583a5736c1df completed May 3, 2026, 4:58 a.m.
NEDg Description generation batch_69f6d76cc33c8190ac8113094bcf868b completed May 3, 2026, 5:04 a.m.
NED2 Entity disambiguation (via description) batch_69f6d8013e9481908f5edcce7247212d completed May 3, 2026, 5:07 a.m.
Created at: April 9, 2026, 9:01 p.m.