Triple

T24197072
Position Surface form Disambiguated ID Type / Status
Subject Ural–Altaic hypothesis E599862 entity
Predicate proposedRelationshipBetween P95416 FINISHED
Object Altaic languages
Altaic languages are a proposed but widely disputed language family that traditionally includes Turkic, Mongolic, and Tungusic languages, and sometimes Korean and Japanese.
E63631 NE FINISHED

How this triple was built (2 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: Altaic languages | Statement: [Ural–Altaic hypothesis, proposedRelationshipBetween, Altaic languages]
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: Altaic languages
Triple: [Ural–Altaic hypothesis, proposedRelationshipBetween, Altaic languages]
Generated description
Altaic languages are a proposed but widely disputed language family that traditionally includes Turkic, Mongolic, and Tungusic languages, and sometimes Korean and Japanese.

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_69e288ceaab88190899d0acb5931591d completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e24c103481908ea49dd8e77dee32 completed April 29, 2026, 10:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbd1180688190a8810bc16ae55c92 completed May 22, 2026, 2:18 a.m.
NEDg Description generation batch_6a0fbdb2afb8819080b49191b6369ec5 completed May 22, 2026, 2:21 a.m.
NED2 Entity disambiguation (via description) batch_6a0fbe63971c81908ab3e446da49765d completed May 22, 2026, 2:24 a.m.
Created at: April 17, 2026, 11:36 p.m.