Triple

T26101407
Position Surface form Disambiguated ID Type / Status
Subject Etzatlán E658410 entity
Predicate borderedBy P224 FINISHED
Object San Juanito de Escobedo Municipality
San Juanito de Escobedo Municipality is an administrative region in the state of Jalisco, Mexico, known for its rural communities and agricultural activities.
E1730695 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: San Juanito de Escobedo Municipality | Statement: [Etzatlán, borderedBy, San Juanito de Escobedo Municipality]
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: San Juanito de Escobedo Municipality
Triple: [Etzatlán, borderedBy, San Juanito de Escobedo Municipality]
Generated description
San Juanito de Escobedo Municipality is an administrative region in the state of Jalisco, Mexico, known for its rural communities and agricultural activities.

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_69ee5bc09c288190bc42a11972841383 completed April 26, 2026, 6:38 p.m.
NER Named-entity recognition batch_69f6073b38a081908607589f0bd9ebed completed May 2, 2026, 2:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c7ebb6208190964277c9b6c4ffe7 completed May 23, 2026, 3:29 p.m.
NEDg Description generation batch_6a11c8d922608190b7b1d32a42e986d5 completed May 23, 2026, 3:33 p.m.
NED2 Entity disambiguation (via description) batch_6a11c99a6eec81909171f7d03a056fc8 completed May 23, 2026, 3:36 p.m.
Created at: April 26, 2026, 7:55 p.m.