Triple

T26100562
Position Surface form Disambiguated ID Type / Status
Subject municipal government of Ameca E658387 entity
Predicate jurisdiction P82 FINISHED
Object municipality of Ameca
The municipality of Ameca is an administrative region in the state of Jalisco, Mexico, centered on the city of Ameca and governed by its own municipal authorities.
E658387 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: municipality of Ameca | Statement: [municipal government of Ameca, jurisdiction, municipality of Ameca]
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: municipality of Ameca
Triple: [municipal government of Ameca, jurisdiction, municipality of Ameca]
Generated description
The municipality of Ameca is an administrative region in the state of Jalisco, Mexico, centered on the city of Ameca and governed by its own municipal authorities.

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_69f6073a39408190994ac1c8983a7c0b completed May 2, 2026, 2:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a111b4424708190b6ad44e1875154cf completed May 23, 2026, 3:13 a.m.
NEDg Description generation batch_6a111c3a2efc8190a6eb67e673603c2b completed May 23, 2026, 3:17 a.m.
NED2 Entity disambiguation (via description) batch_6a111cdb99b48190887114a6ec92a03f completed May 23, 2026, 3:19 a.m.
Created at: April 26, 2026, 7:54 p.m.