Triple

T33547532
Position Surface form Disambiguated ID Type / Status
Subject Catherine Anne Phipps E859244 entity
Predicate honorificPrefixByMarriage P150114 FINISHED
Object Lady Prevost
Lady Prevost is the married title of Catherine Anne Phipps, a British woman who became part of the aristocracy through her union with a titled husband.
 E2055127 NE FINISHED

How this triple was built (3 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: Lady Prevost | Statement: [Catherine Anne Phipps, honorificPrefixByMarriage, Lady Prevost]
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: Lady Prevost
Triple: [Catherine Anne Phipps, honorificPrefixByMarriage, Lady Prevost]
Generated description
Lady Prevost is the married title of Catherine Anne Phipps, a British woman who became part of the aristocracy through her union with a titled husband.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: honorificPrefixByMarriage
Context triple: [Catherine Anne Phipps, honorificPrefixByMarriage, Lady Prevost]
  • A. honorificPrefixOfSpouse chosen
    Indicates that a specified honorific prefix (e.g., Mr., Dr., Lady) is used as the formal title for a person’s spouse.
  • B. honorificPrefix
    Indicates the formal title or respectful prefix (e.g., "Dr.", "Mr.", "Prof.") used before a person's name to denote status, role, or honor.
  • C. honorificSuffix
    Indicates that one entity is a respectful or formal suffix appended to another entity’s name or title.
  • D. honorificPartOfName
    Indicates that an honorific title or form of address is included as part of a person's full name.
  • E. honorificPrefixOfFather
    Indicates that the subject is an honorific prefix or title used before the name of the object’s father.
  • F. None of above.

Provenance (6 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_69f3497a5be08190a39b12736899e034 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f74062b9388190b30546cf700a825c completed May 3, 2026, 12:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a35a68cc7948190bb528e8da54ca499 completed June 19, 2026, 8:29 p.m.
NEDg Description generation batch_6a35a71051648190a33ed02afc5c6798 completed June 19, 2026, 8:31 p.m.
NED2 Entity disambiguation (via description) batch_6a35a7da68bc819090b95df78ec28e57 completed June 19, 2026, 8:34 p.m.
PD Predicate disambiguation batch_69f73c802b848190b61a416b7488bd96 completed May 3, 2026, 12:16 p.m.
Created at: May 1, 2026, 1:39 a.m.