Triple

T32161974
Position Surface form Disambiguated ID Type / Status
Subject Guaicuruan languages E821451 entity
Predicate associatedEthnicGroups P12220 FINISHED
Object Pilagá people
The Pilagá people are an Indigenous group of the Gran Chaco region in northern Argentina, known for their distinct cultural traditions and Guaicuruan language.
E2050498 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: Pilagá people | Statement: [Guaicuruan languages, associatedEthnicGroups, Pilagá people]
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: Pilagá people
Triple: [Guaicuruan languages, associatedEthnicGroups, Pilagá people]
Generated description
The Pilagá people are an Indigenous group of the Gran Chaco region in northern Argentina, known for their distinct cultural traditions and Guaicuruan language.

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_69f34905e098819082191a6922a6d607 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6ba1b75748190af3f7df0cd0ed2a9 completed May 3, 2026, 2:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35812eb9048190851cbe7e71ad5623 completed June 19, 2026, 5:49 p.m.
NEDg Description generation batch_6a3581ddeab88190b15f2f974ef67e0e completed June 19, 2026, 5:52 p.m.
NED2 Entity disambiguation (via description) batch_6a3582372b908190be6d6197e7e4ea92 completed June 19, 2026, 5:53 p.m.
Created at: May 1, 2026, 12:32 a.m.