Triple

T33561532
Position Surface form Disambiguated ID Type / Status
Subject Maravatío E859635 entity
Predicate capitalOf P204 FINISHED
Object Maravatío Municipality
Maravatío Municipality is an administrative division in the state of Michoacán, Mexico, centered around the town of Maravatío and encompassing the surrounding rural and urban areas.
E2058996 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: Maravatío Municipality | Statement: [Maravatío, capitalOf, Maravatío 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: Maravatío Municipality
Triple: [Maravatío, capitalOf, Maravatío Municipality]
Generated description
Maravatío Municipality is an administrative division in the state of Michoacán, Mexico, centered around the town of Maravatío and encompassing the surrounding rural and urban areas.

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_69f3497c1d288190a844ea699914e038 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f7127d848190916a5a45fe3b6578 completed May 3, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36118a984881908feb801212e5a2b6 completed June 20, 2026, 4:05 a.m.
NEDg Description generation batch_6a361278b19081908401979fdf6960fb completed June 20, 2026, 4:09 a.m.
NED2 Entity disambiguation (via description) batch_6a361320704c8190a63a2aa5e1f11093 completed June 20, 2026, 4:12 a.m.
Created at: May 1, 2026, 1:40 a.m.