Triple

T15466671
Position Surface form Disambiguated ID Type / Status
Subject Hupa language E372046 entity
Predicate closelyRelatedTo P37 FINISHED
Object Kato language
Kato language is an extinct Athabaskan (Na-Dene) language once spoken by the Kato people of northern California.
 E1159083 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: Kato language | Statement: [Hupa language, closelyRelatedTo, Kato language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kato language
Context triple: [Hupa language, closelyRelatedTo, Kato language]
  • A. Katu language
    Katu language is an Austroasiatic language spoken by the Katu people primarily in Laos and central Vietnam.
  • B. Kati language
    The Kati language is a Nuristani language spoken primarily in parts of northeastern Afghanistan and adjacent regions of Pakistan.
  • C. Kawaiisu language
    Kawaiisu language is an endangered Uto-Aztecan language traditionally spoken by the Kawaiisu people of southern California.
  • D. Mikasuki language
    The Mikasuki language is a Native American Muskogean language traditionally spoken by the Miccosukee and Seminole peoples of Florida.
  • E. Akawaio language
    The Akawaio language is an indigenous Cariban language spoken by the Akawaio people of Guyana, Venezuela, and Brazil.
  • 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: Kato language
Triple: [Hupa language, closelyRelatedTo, Kato language]
Generated description
Kato language is an extinct Athabaskan (Na-Dene) language once spoken by the Kato people of northern California.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kato language
Target entity description: Kato language is an extinct Athabaskan (Na-Dene) language once spoken by the Kato people of northern California.
  • A. Katu language
    Katu language is an Austroasiatic language spoken by the Katu people primarily in Laos and central Vietnam.
  • B. Kati language
    The Kati language is a Nuristani language spoken primarily in parts of northeastern Afghanistan and adjacent regions of Pakistan.
  • C. Kawaiisu language
    Kawaiisu language is an endangered Uto-Aztecan language traditionally spoken by the Kawaiisu people of southern California.
  • D. Mikasuki language
    The Mikasuki language is a Native American Muskogean language traditionally spoken by the Miccosukee and Seminole peoples of Florida.
  • E. Akawaio language
    The Akawaio language is an indigenous Cariban language spoken by the Akawaio people of Guyana, Venezuela, and Brazil.
  • 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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f69a31c81909a749247b6615d91 completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2d01a23c819095cf75b7d5a801a9 completed May 9, 2026, 12:48 p.m.
NEDg Description generation batch_69ff2e1fb27c81908de0d755bf30c833 completed May 9, 2026, 12:52 p.m.
NED2 Entity disambiguation (via description) batch_69ff2f3ab6988190b4cefe2f55c4101c completed May 9, 2026, 12:57 p.m.
Created at: April 10, 2026, 3:33 a.m.