Triple

T6728579
Position Surface form Disambiguated ID Type / Status
Subject Vietic languages E153577 entity
Predicate hasMember P10 FINISHED
Object Rục language
Rục language is a highly endangered Vietic language spoken by the small Rục ethnic group in the mountainous regions of central Vietnam.
 E615583 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: Rục language | Statement: [Vietic languages, hasMember, Rục language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rục language
Context triple: [Vietic languages, hasMember, Rục language]
  • A. Rumsen language
    Rumsen language is an extinct Ohlone (Costanoan) Native American language formerly spoken in the Monterey Bay area of California.
  • B. Rarámuri language
    The Rarámuri language is an indigenous Uto-Aztecan language spoken by the Tarahumara (Rarámuri) people of northern Mexico.
  • C. Munduruku language
    The Munduruku language is an indigenous Tupian language spoken by the Munduruku people of the Amazon region in Brazil.
  • D. Logba language
    The Logba language is a Niger-Congo language spoken by the Logba people of southeastern Ghana.
  • E. Tujia language
    The Tujia language is a Sino-Tibetan language spoken primarily by the Tujia ethnic group in parts of central China, notably in mountainous areas of Hubei, Hunan, and neighboring provinces.
  • 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: Rục language
Triple: [Vietic languages, hasMember, Rục language]
Generated description
Rục language is a highly endangered Vietic language spoken by the small Rục ethnic group in the mountainous regions of central Vietnam.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rục language
Target entity description: Rục language is a highly endangered Vietic language spoken by the small Rục ethnic group in the mountainous regions of central Vietnam.
  • A. Rumsen language
    Rumsen language is an extinct Ohlone (Costanoan) Native American language formerly spoken in the Monterey Bay area of California.
  • B. Rarámuri language
    The Rarámuri language is an indigenous Uto-Aztecan language spoken by the Tarahumara (Rarámuri) people of northern Mexico.
  • C. Munduruku language
    The Munduruku language is an indigenous Tupian language spoken by the Munduruku people of the Amazon region in Brazil.
  • D. Logba language
    The Logba language is a Niger-Congo language spoken by the Logba people of southeastern Ghana.
  • E. Tujia language
    The Tujia language is a Sino-Tibetan language spoken primarily by the Tujia ethnic group in parts of central China, notably in mountainous areas of Hubei, Hunan, and neighboring provinces.
  • 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_69c6880bdd68819097de8b6099992682 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d153ef9c8190a31021227d814d82 completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70b00ba9c8190aaae2220972ff4f2 completed March 27, 2026, 10:56 p.m.
NEDg Description generation batch_69c70c5fc9c88190ba499b0a9e7bcbc2 completed March 27, 2026, 11:01 p.m.
NED2 Entity disambiguation (via description) batch_69c70d0fcbc08190b3a7d0de3c634a5f completed March 27, 2026, 11:04 p.m.
Created at: March 27, 2026, 2:08 p.m.