Triple

T11605478
Position Surface form Disambiguated ID Type / Status
Subject Lamar Lundy E275246 entity
Predicate givenName P17 FINISHED
Object Lamar
Lamar is a masculine given name of Old French and Old German origin, commonly used in the United States.
E936969 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: [Lamar Lundy, givenName, Lamar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lamar
Context triple: [Lamar Lundy, givenName, Lamar]
  • A. Lamar
    Lamar is a surname most notably associated with Mirabeau B. Lamar, the second president of the Republic of Texas.
  • B. Lamar
    Lamar is a small city in southeastern Colorado that serves as an agricultural and transportation hub for the surrounding rural region.
  • C. Gatlin
    Gatlin is a surname of English origin borne by various notable individuals across fields such as music, sports, and politics.
  • D. Parmer
    Parmer is a surname and place name that serves as a variant spelling of Palmer.
  • E. Brantley
    Brantley is a small town located in Crenshaw County in the state of Alabama, United States.
  • 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: [Lamar Lundy, givenName, Lamar]
Generated description
Lamar is a masculine given name of Old French and Old German origin, commonly used in the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lamar
Target entity description: Lamar is a masculine given name of Old French and Old German origin, commonly used in the United States.
  • A. Lamar
    Lamar is a surname most notably associated with Mirabeau B. Lamar, the second president of the Republic of Texas.
  • B. Lamar
    Lamar is a small city in southeastern Colorado that serves as an agricultural and transportation hub for the surrounding rural region.
  • C. Gatlin
    Gatlin is a surname of English origin borne by various notable individuals across fields such as music, sports, and politics.
  • D. Parmer
    Parmer is a surname and place name that serves as a variant spelling of Palmer.
  • E. Brantley
    Brantley is a small town located in Crenshaw County in the state of Alabama, United States.
  • 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_69d6aaf84b548190ac072e4fb89ae18f completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d895502e0081909ee9c3d45d26cd91 completed April 10, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee87077d008190874a8339b64dd5ec completed April 26, 2026, 9:43 p.m.
NEDg Description generation batch_69ee9cf1cb2481908bc473c87bc42d60 completed April 26, 2026, 11:17 p.m.
NED2 Entity disambiguation (via description) batch_69eecd31894481908dbd55f605c693f9 completed April 27, 2026, 2:42 a.m.
Created at: April 8, 2026, 9:38 p.m.