Triple

T915116
Position Surface form Disambiguated ID Type / Status
Subject Clarence Darrow E19751 entity
Predicate givenName P17 FINISHED
Object Clarence
Clarence is a masculine given name of Latin origin, commonly used in English-speaking countries.
 E151400 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: Clarence | Statement: [Clarence Darrow, givenName, Clarence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Clarence
Context triple: [Clarence Darrow, givenName, Clarence]
  • A. Henry
    Henry is the given name of Henry A. Kissinger, the influential American diplomat and political scientist who served as U.S. Secretary of State and National Security Advisor.
  • B. Edward
    Edward is a masculine given name of English origin, historically associated with kings of England and notable figures such as U.S. Senator Edward M. Kennedy.
  • C. Thomas
    Thomas is the given name of Confederate General "Stonewall" Jackson, a prominent military leader during the American Civil War.
  • D. Thomas
    Thomas is the given name of Thomas Cranmer, the 16th-century Archbishop of Canterbury and a leading figure in the English Reformation.
  • E. Thomas
    Thomas is a common masculine given name of Aramaic origin, widely used in English-speaking and many other cultures.
  • 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: Clarence
Triple: [Clarence Darrow, givenName, Clarence]
Generated description
Clarence is a masculine given name of Latin origin, commonly used in English-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Clarence
Target entity description: Clarence is a masculine given name of Latin origin, commonly used in English-speaking countries.
  • A. Henry
    Henry is the given name of Henry A. Kissinger, the influential American diplomat and political scientist who served as U.S. Secretary of State and National Security Advisor.
  • B. Edward
    Edward is a masculine given name of English origin, historically associated with kings of England and notable figures such as U.S. Senator Edward M. Kennedy.
  • C. Thomas
    Thomas is the given name of Confederate General "Stonewall" Jackson, a prominent military leader during the American Civil War.
  • D. Thomas
    Thomas is the given name of Thomas Cranmer, the 16th-century Archbishop of Canterbury and a leading figure in the English Reformation.
  • E. Thomas
    Thomas is a common masculine given name of Aramaic origin, widely used in English-speaking and many other cultures.
  • 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_69a4939f91a08190ba68c2c81eab90fe completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b2f605bc8190a5245aa2ca55cf43 completed March 1, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbf0949c481908868bd27eeb964b4 completed March 8, 2026, 12:12 a.m.
NEDg Description generation batch_69acbfdaaa548190a9b8d74bf1651df1 completed March 8, 2026, 12:16 a.m.
NED2 Entity disambiguation (via description) batch_69acc04ff3bc819083df91a13ea63679 completed March 8, 2026, 12:18 a.m.
Created at: March 1, 2026, 7:39 p.m.