Triple

T356210
Position Surface form Disambiguated ID Type / Status
Subject Mirabeau B. Lamar E7547 entity
Predicate familyName P18 FINISHED
Object Lamar
Lamar is a surname most notably associated with Mirabeau B. Lamar, the second president of the Republic of Texas.
 E45230 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: Lamar | Statement: [Mirabeau B. Lamar, familyName, Lamar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lamar
Context triple: [Mirabeau B. Lamar, familyName, Lamar]
  • A. Lamon
    Lamon is an archaeological site notable for inscriptions in the ancient Venetic language.
  • B. Randall Woodfin
    Randall Woodfin is an American politician and attorney who serves as the progressive, reform-focused mayor of Birmingham, Alabama.
  • C. Roscoe
    "Roscoe" is an essay by Washington Irving, included in his collection *The Sketch Book of Geoffrey Crayon, Gent.*, that reflects on the life and character of English historian and writer William Roscoe.
  • D. Richardson
    Richardson is a suburban city in the Dallas–Fort Worth metropolitan area known for its telecommunications industry and the University of Texas at Dallas.
  • E. Lawrence
    Lawrence is a historic mill city in northeastern Massachusetts that developed as a major textile manufacturing center along the Merrimack River.
  • 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: Lamar
Triple: [Mirabeau B. Lamar, familyName, Lamar]
Generated description
Lamar is a surname most notably associated with Mirabeau B. Lamar, the second president of the Republic of Texas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lamar
Target entity description: Lamar is a surname most notably associated with Mirabeau B. Lamar, the second president of the Republic of Texas.
  • A. Lamon
    Lamon is an archaeological site notable for inscriptions in the ancient Venetic language.
  • B. Randall Woodfin
    Randall Woodfin is an American politician and attorney who serves as the progressive, reform-focused mayor of Birmingham, Alabama.
  • C. Roscoe
    "Roscoe" is an essay by Washington Irving, included in his collection *The Sketch Book of Geoffrey Crayon, Gent.*, that reflects on the life and character of English historian and writer William Roscoe.
  • D. Richardson
    Richardson is a suburban city in the Dallas–Fort Worth metropolitan area known for its telecommunications industry and the University of Texas at Dallas.
  • E. Lawrence
    Lawrence is a historic mill city in northeastern Massachusetts that developed as a major textile manufacturing center along the Merrimack River.
  • 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_69a2e7e696948190bebc966535995e45 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebad8bf08190b4a38ffd9157d641 completed Feb. 28, 2026, 1:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3e019211c819087edeb99431061fa completed March 1, 2026, 6:43 a.m.
NEDg Description generation batch_69a3e1092bc48190bd2d4b59d30b8c64 completed March 1, 2026, 6:47 a.m.
NED2 Entity disambiguation (via description) batch_69a3e2183bec8190b1d93a02ec8a0ab8 completed March 1, 2026, 6:52 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.