Triple

T32105449
Position Surface form Disambiguated ID Type / Status
Subject Santa María Pápalo Cuicatec E819968 entity
Predicate hasAncestor P369 FINISHED
Object Proto-Cuicatec language
Proto-Cuicatec language is the reconstructed ancestral language from which the modern Cuicatec varieties of Oaxaca, Mexico, are derived.
E1993930 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: Proto-Cuicatec language | Statement: [Santa María Pápalo Cuicatec, hasAncestor, Proto-Cuicatec language]
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: Proto-Cuicatec language
Triple: [Santa María Pápalo Cuicatec, hasAncestor, Proto-Cuicatec language]
Generated description
Proto-Cuicatec language is the reconstructed ancestral language from which the modern Cuicatec varieties of Oaxaca, Mexico, are derived.

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_69f34901106881908ea893ad504a08be completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b699af5c8190b1e803472ddb3ded completed May 3, 2026, 2:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f012203048190b77b0e29fc09bc05 completed June 14, 2026, 7:29 p.m.
NEDg Description generation batch_6a2f01c288648190bacd6fbdf933732e completed June 14, 2026, 7:32 p.m.
NED2 Entity disambiguation (via description) batch_6a2f033489248190bc282c71f5ad618c completed June 14, 2026, 7:38 p.m.
Created at: May 1, 2026, 12:27 a.m.