Triple

T24993172
Position Surface form Disambiguated ID Type / Status
Subject Sombrerete E625499 entity
Predicate hasLandmark P105 FINISHED
Object Parroquia de San Juan Bautista
Parroquia de San Juan Bautista is a historic Catholic parish church and prominent religious landmark located in the town of Sombrerete, Mexico.
E1661799 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: Parroquia de San Juan Bautista | Statement: [Sombrerete, hasLandmark, Parroquia de San Juan Bautista]
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: Parroquia de San Juan Bautista
Triple: [Sombrerete, hasLandmark, Parroquia de San Juan Bautista]
Generated description
Parroquia de San Juan Bautista is a historic Catholic parish church and prominent religious landmark located in the town of Sombrerete, 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_69e2ff2611c081908710457fbe6d376b completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44a4787948190874b230f692d16c7 completed May 1, 2026, 6:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1048a96d608190a01f1c1476525b69 completed May 22, 2026, 12:14 p.m.
NEDg Description generation batch_6a1049b63de881908e04b30b555d7809 completed May 22, 2026, 12:19 p.m.
NED2 Entity disambiguation (via description) batch_6a104a82de208190b720e5690a5094c0 completed May 22, 2026, 12:22 p.m.
Created at: April 18, 2026, 6:04 a.m.