Triple

T15909714
Position Surface form Disambiguated ID Type / Status
Subject Mrs. George E385813 entity
Predicate spouse P13 FINISHED
Object Mr. George
Mr. George is a married individual known primarily as the husband of Mrs. George.
E1183749 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: Mr. George | Statement: [Mrs. George, spouse, Mr. George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mr. George
Context triple: [Mrs. George, spouse, Mr. George]
  • A. Grandpa George
    Grandpa George is one of Charlie Bucket’s elderly, bedridden grandparents in Roald Dahl’s novel "Charlie and the Chocolate Factory."
  • B. Mr. Brown
    Mr. Brown is the kind-hearted but often flustered father figure from the "Paddington" film series.
  • C. Mr. Brown
    Mr. Brown is one of the color-coded hijackers in the crime thriller "The Taking of Pelham One Two Three," known for his role in the subway train hostage plot.
  • D. Mr. Brown
    Mr. Brown is a comically eccentric, churchgoing older man known for his loud outfits, over-the-top reactions, and frequent appearances in Tyler Perry’s Madea franchise.
  • E. Uncle George
    Uncle George is a central family figure in Eudora Welty’s novel "Delta Wedding," around whom much of the Fairchild clan’s domestic life and emotional dynamics revolve.
  • 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: Mr. George
Triple: [Mrs. George, spouse, Mr. George]
Generated description
Mr. George is a married individual known primarily as the husband of Mrs. George.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mr. George
Target entity description: Mr. George is a married individual known primarily as the husband of Mrs. George.
  • A. Grandpa George
    Grandpa George is one of Charlie Bucket’s elderly, bedridden grandparents in Roald Dahl’s novel "Charlie and the Chocolate Factory."
  • B. Mr. Brown
    Mr. Brown is the kind-hearted but often flustered father figure from the "Paddington" film series.
  • C. Mr. Brown
    Mr. Brown is one of the color-coded hijackers in the crime thriller "The Taking of Pelham One Two Three," known for his role in the subway train hostage plot.
  • D. Mr. Brown
    Mr. Brown is a comically eccentric, churchgoing older man known for his loud outfits, over-the-top reactions, and frequent appearances in Tyler Perry’s Madea franchise.
  • E. Uncle George
    Uncle George is a central family figure in Eudora Welty’s novel "Delta Wedding," around whom much of the Fairchild clan’s domestic life and emotional dynamics revolve.
  • 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_69d86da686e4819097cbf3b1fc2d881d completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1565ea7a8819097efffda366b5245 completed April 16, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb05750ac81908860143f4ca26cc7 completed May 9, 2026, 10:08 p.m.
NEDg Description generation batch_69ffb110a5b88190904f763057e8eb1e completed May 9, 2026, 10:11 p.m.
NED2 Entity disambiguation (via description) batch_69ffb1a5e9b88190b790c81b9500c2ac completed May 9, 2026, 10:13 p.m.
Created at: April 10, 2026, 4:52 a.m.