Triple

T28770819
Position Surface form Disambiguated ID Type / Status
Subject Western Chatino E726407 entity
Predicate hasDialect P4251 FINISHED
Object Juquila Chatino
Juquila Chatino is a variant of the Chatino language spoken by indigenous communities in the Juquila region of Oaxaca, Mexico.
E1841075 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: Juquila Chatino | Statement: [Western Chatino, hasDialect, Juquila Chatino]
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: Juquila Chatino
Triple: [Western Chatino, hasDialect, Juquila Chatino]
Generated description
Juquila Chatino is a variant of the Chatino language spoken by indigenous communities in the Juquila region of Oaxaca, Mexico.

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_69f03198be14819098fa74e48b3749bf completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f65827a4fc8190b0bd1914655502d6 completed May 2, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24ec259194819099e88671bf411c73 completed June 7, 2026, 3:57 a.m.
NEDg Description generation batch_6a24f01d17108190a7979d7b18ffd829 completed June 7, 2026, 4:14 a.m.
NED2 Entity disambiguation (via description) batch_6a24f3d649248190b5db267c8eae8486 completed June 7, 2026, 4:30 a.m.
Created at: April 28, 2026, 6:15 a.m.