Triple

T616088
Position Surface form Disambiguated ID Type / Status
Subject Mayaimi people E14406 entity
Predicate nameVariant P744 FINISHED
Object Mayami
Mayami is a historical Native American people who lived around Lake Okeechobee in what is now southern Florida.
 E77088 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: Mayami | Statement: [Mayaimi people, nameVariant, Mayami]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mayami
Context triple: [Mayaimi people, nameVariant, Mayami]
  • A. Hana
    Hana is a compassionate Canadian army nurse in Michael Ondaatje's novel "The English Patient," who cares for a badly burned man in an abandoned Italian villa during World War II.
  • B. Minna
    Minna is a major city and administrative center in north-central Nigeria, known as the capital of Niger State and a regional hub for trade and transportation.
  • C. Sojin Kamiyama
    Sojin Kamiyama was a Japanese actor of the silent film era, best known for his prominent roles in early Hollywood productions.
  • D. Maia
    Maia is a figure from Greek mythology, one of the Pleiades and the mother of the god Hermes.
  • E. Mariko Suga
    Mariko Suga is the wife of former Japanese Prime Minister Yoshihide Suga and a largely private figure outside of her role as his spouse.
  • 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: Mayami
Triple: [Mayaimi people, nameVariant, Mayami]
Generated description
Mayami is a historical Native American people who lived around Lake Okeechobee in what is now southern Florida.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mayami
Target entity description: Mayami is a historical Native American people who lived around Lake Okeechobee in what is now southern Florida.
  • A. Hana
    Hana is a compassionate Canadian army nurse in Michael Ondaatje's novel "The English Patient," who cares for a badly burned man in an abandoned Italian villa during World War II.
  • B. Minna
    Minna is a major city and administrative center in north-central Nigeria, known as the capital of Niger State and a regional hub for trade and transportation.
  • C. Sojin Kamiyama
    Sojin Kamiyama was a Japanese actor of the silent film era, best known for his prominent roles in early Hollywood productions.
  • D. Maia
    Maia is a figure from Greek mythology, one of the Pleiades and the mother of the god Hermes.
  • E. Mariko Suga
    Mariko Suga is the wife of former Japanese Prime Minister Yoshihide Suga and a largely private figure outside of her role as his spouse.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e22f3688190a512bec3f0347814 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5554b4f888190b9b64ece37087bf4 completed March 2, 2026, 9:15 a.m.
NEDg Description generation batch_69a555ae08b88190aad64ec7923437ef completed March 2, 2026, 9:17 a.m.
NED2 Entity disambiguation (via description) batch_69a556669878819098816d2221a3fd3d completed March 2, 2026, 9:20 a.m.
Created at: March 1, 2026, 7:35 p.m.