Triple

T1048017
Position Surface form Disambiguated ID Type / Status
Subject Mary Higgins Clark E22627 entity
Predicate familyName P18 FINISHED
Object Clark
Clark is a common English-language surname borne by numerous notable individuals across fields such as literature, politics, science, and entertainment.
 E119775 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: Clark | Statement: [Mary Higgins Clark, familyName, Clark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Clark
Context triple: [Mary Higgins Clark, familyName, Clark]
  • A. Clark
    Clark is the middle name of Herbert Hoover, the 31st president of the United States.
  • B. Clayton
    Clayton is a district in east Manchester, England, known for its residential character and proximity to the city’s industrial and sporting landmarks.
  • C. Clayton
    Clayton is a town in Johnston County, North Carolina, known as a growing suburban community within the Raleigh metropolitan area.
  • D. Clayton
    Clayton is the protagonist of Harriet Beecher Stowe’s anti-slavery novel "Dred: A Tale of the Great Dismal Swamp," through whom themes of morality, justice, and the complexities of slavery are explored.
  • E. Clark/Lake
    Clark/Lake is a major Chicago 'L' rapid transit station in the Loop that serves multiple CTA lines and functions as a key downtown transfer hub.
  • 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: Clark
Triple: [Mary Higgins Clark, familyName, Clark]
Generated description
Clark is a common English-language surname borne by numerous notable individuals across fields such as literature, politics, science, and entertainment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Clark
Target entity description: Clark is a common English-language surname borne by numerous notable individuals across fields such as literature, politics, science, and entertainment.
  • A. Clark
    Clark is the middle name of Herbert Hoover, the 31st president of the United States.
  • B. Clayton
    Clayton is a district in east Manchester, England, known for its residential character and proximity to the city’s industrial and sporting landmarks.
  • C. Clayton
    Clayton is a town in Johnston County, North Carolina, known as a growing suburban community within the Raleigh metropolitan area.
  • D. Clayton
    Clayton is the protagonist of Harriet Beecher Stowe’s anti-slavery novel "Dred: A Tale of the Great Dismal Swamp," through whom themes of morality, justice, and the complexities of slavery are explored.
  • E. Clark/Lake
    Clark/Lake is a major Chicago 'L' rapid transit station in the Loop that serves multiple CTA lines and functions as a key downtown transfer hub.
  • 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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8b19a5c8190a532e025bd724088 completed March 1, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3bcb65d08190b2ea04b6de3bb39b completed March 7, 2026, 2:52 p.m.
NEDg Description generation batch_69ac3ce6228881908f429cb0a016a17a completed March 7, 2026, 2:57 p.m.
NED2 Entity disambiguation (via description) batch_69ac3d3ed140819087ede15c555e2f4d completed March 7, 2026, 2:59 p.m.
Created at: March 1, 2026, 7:42 p.m.