Triple

T29128537
Position Surface form Disambiguated ID Type / Status
Subject Chiquitos region E738301 entity
Predicate hasTown P847 FINISHED
Object Santa Ana de Velasco
Santa Ana de Velasco is a historic mission town in eastern Bolivia, known for its well-preserved Jesuit architecture and cultural heritage within the Chiquitos region.
E1859896 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: Santa Ana de Velasco | Statement: [Chiquitos region, hasTown, Santa Ana de Velasco]
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: Santa Ana de Velasco
Triple: [Chiquitos region, hasTown, Santa Ana de Velasco]
Generated description
Santa Ana de Velasco is a historic mission town in eastern Bolivia, known for its well-preserved Jesuit architecture and cultural heritage within the Chiquitos region.

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_69f07cb29cdc8190afa55444553de60c completed April 28, 2026, 9:24 a.m.
NER Named-entity recognition batch_69f6622c2e1c819093b43ecb65f3fa52 completed May 2, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25890c1b748190824ba7c8a4d68615 completed June 7, 2026, 3:06 p.m.
NEDg Description generation batch_6a25944a643c8190b5458a00aa75a9fc completed June 7, 2026, 3:54 p.m.
NED2 Entity disambiguation (via description) batch_6a25949da2f88190bab7ab9362f3c3d8 completed June 7, 2026, 3:56 p.m.
Created at: April 28, 2026, 11:30 a.m.