Triple

T24888623
Position Surface form Disambiguated ID Type / Status
Subject Anne Bourchier, 7th Baroness Bourchier E622929 entity
Predicate hadLover P23617 FINISHED
Object John Lyngfield
John Lyngfield was a 16th-century English cleric and prior of St. Mary Overy in Southwark, best known for his scandalous relationship with Anne Bourchier, 7th Baroness Bourchier.
 E1649587 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: John Lyngfield | Statement: [Anne Bourchier, 7th Baroness Bourchier, hadLover, John Lyngfield]
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: John Lyngfield
Triple: [Anne Bourchier, 7th Baroness Bourchier, hadLover, John Lyngfield]
Generated description
John Lyngfield was a 16th-century English cleric and prior of St. Mary Overy in Southwark, best known for his scandalous relationship with Anne Bourchier, 7th Baroness Bourchier.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hadLover
Context triple: [Anne Bourchier, 7th Baroness Bourchier, hadLover, John Lyngfield]
  • A. hadPartner
    Indicates that an entity was in a romantic or life-partner relationship with another entity at some point in time.
  • B. hadPartnerType
    Indicates that an entity was associated with another entity in a specific type or category of partnership.
  • C. hasAffairWith chosen
    Indicates that one entity is engaged in a secret or illicit romantic or sexual relationship with another entity, typically outside a committed partnership.
  • D. hasBeenDatedBy
    Indicates that one entity has previously been in a romantic or dating relationship with another entity.
  • E. hasSex
    Indicates that one entity engages in sexual activity with another entity.
  • 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_69e2fac597708190a922bf39a49ec70a completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f43043512481909501a3979cac9947 completed May 1, 2026, 4:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c6a981c81909eca63e109ab6971 completed May 22, 2026, 9:05 a.m.
NEDg Description generation batch_6a10229229a481909ebb009ce5932e8b completed May 22, 2026, 9:32 a.m.
NED2 Entity disambiguation (via description) batch_6a102388612c81909fda138f132409a3 completed May 22, 2026, 9:36 a.m.
PD Predicate disambiguation batch_69f420fd375c81908ea4a4e60b76ee8f completed May 1, 2026, 3:41 a.m.
Created at: April 18, 2026, 5:25 a.m.