Triple

T35061985
Position Surface form Disambiguated ID Type / Status
Subject Calamuchita Department E1011617 entity
Predicate hasTouristTown P30296 FINISHED
Object Santa Rosa de Calamuchita
Santa Rosa de Calamuchita is a popular riverside tourist town in the Calamuchita Valley of Córdoba Province, Argentina, known for its natural scenery and outdoor recreation.
E2126295 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 Rosa de Calamuchita | Statement: [Calamuchita Department, hasTouristTown, Santa Rosa de Calamuchita]
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 Rosa de Calamuchita
Triple: [Calamuchita Department, hasTouristTown, Santa Rosa de Calamuchita]
Generated description
Santa Rosa de Calamuchita is a popular riverside tourist town in the Calamuchita Valley of Córdoba Province, Argentina, known for its natural scenery and outdoor recreation.

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_69f76dd09c308190a523454853ce842b completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7860db9a881909ff887028b57acde completed May 3, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37cfe37a808190ae7843090f30430d completed June 21, 2026, 11:49 a.m.
NEDg Description generation batch_6a37d0c6633c81909a7d803ece43f548 completed June 21, 2026, 11:53 a.m.
NED2 Entity disambiguation (via description) batch_6a37d3792f2c81909ae28634bbc0c47a completed June 21, 2026, 12:05 p.m.
Created at: May 3, 2026, 4:01 p.m.