Triple

T19429556
Position Surface form Disambiguated ID Type / Status
Subject Western Keres E486073 entity
Predicate subclassOf P1244 FINISHED
Object Keres language
The Keres language is a group of closely related Indigenous languages spoken by the Keresan Pueblo peoples of New Mexico.
 E1375692 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: Keres language | Statement: [Western Keres, subclassOf, Keres language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Keres language
Context triple: [Western Keres, subclassOf, Keres language]
  • A. Kerek language
    The Kerek language is an extinct Chukotko-Kamchatkan language once spoken by the Kerek people of northeastern Siberia in Russia.
  • B. Kayeli language
    The Kayeli language is an Austronesian language once spoken on Buru Island in Indonesia, now critically endangered or possibly extinct.
  • C. Kaera language
    The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
  • D. Kerewe language
    The Kerewe language is a Bantu language spoken primarily by the Kerewe people on Ukerewe Island in Lake Victoria, Tanzania.
  • E. Teke-Kega language
    The Teke-Kega language is a Bantu language spoken by the Teke people of Central Africa, primarily in the Republic of the Congo and surrounding regions.
  • 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: Keres language
Triple: [Western Keres, subclassOf, Keres language]
Generated description
The Keres language is a group of closely related Indigenous languages spoken by the Keresan Pueblo peoples of New Mexico.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Keres language
Target entity description: The Keres language is a group of closely related Indigenous languages spoken by the Keresan Pueblo peoples of New Mexico.
  • A. Kerek language
    The Kerek language is an extinct Chukotko-Kamchatkan language once spoken by the Kerek people of northeastern Siberia in Russia.
  • B. Kayeli language
    The Kayeli language is an Austronesian language once spoken on Buru Island in Indonesia, now critically endangered or possibly extinct.
  • C. Kaera language
    The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
  • D. Kerewe language
    The Kerewe language is a Bantu language spoken primarily by the Kerewe people on Ukerewe Island in Lake Victoria, Tanzania.
  • E. Teke-Kega language
    The Teke-Kega language is a Bantu language spoken by the Teke people of Central Africa, primarily in the Republic of the Congo and surrounding regions.
  • 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_69d8e8d688f881909c85104a62e09d8a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6321b78d08190b86cef7c60cbb61c completed April 20, 2026, 2:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0733d867a88190b04e3de929cddc20 completed May 15, 2026, 2:55 p.m.
NEDg Description generation batch_6a07350fbcdc8190bf7a006b52de0508 completed May 15, 2026, 3 p.m.
NED2 Entity disambiguation (via description) batch_6a0735a000c88190a5fac2af7f93907b completed May 15, 2026, 3:02 p.m.
Created at: April 10, 2026, 1:37 p.m.