Triple

T38047202
Position Surface form Disambiguated ID Type / Status
Subject Yaracuy state E949649 entity
Predicate hasMunicipality P847 FINISHED
Object San Felipe Municipality
San Felipe Municipality is an administrative division in north-central Venezuela that includes the city of San Felipe, the capital of Yaracuy state.
E2261854 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 Felipe Municipality | Statement: [Yaracuy state, hasMunicipality, San Felipe 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 Felipe Municipality
Triple: [Yaracuy state, hasMunicipality, San Felipe Municipality]
Generated description
San Felipe Municipality is an administrative division in north-central Venezuela that includes the city of San Felipe, the capital of Yaracuy state.

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_69f76f000cf081908c11fb5443b392e6 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbc9db306081909919bed2bb492b84 completed May 6, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4193b3907881908ff7ba8e3596aff4 completed June 28, 2026, 9:35 p.m.
NEDg Description generation batch_6a419422d7788190972c228a5bc59de2 completed June 28, 2026, 9:37 p.m.
NED2 Entity disambiguation (via description) batch_6a4194ae849c8190ad01ba5ede914085 completed June 28, 2026, 9:39 p.m.
Created at: May 3, 2026, 4:20 p.m.