Triple

T27789767
Position Surface form Disambiguated ID Type / Status
Subject Judicial branch of Nuevo León E701048 entity
Predicate partOf P40 FINISHED
Object Government of Nuevo León
The Government of Nuevo León is the state-level governing authority of Nuevo León, Mexico, encompassing its executive, legislative, and judicial branches.
E1788898 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: Government of Nuevo León | Statement: [Judicial branch of Nuevo León, partOf, Government of Nuevo León]
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: Government of Nuevo León
Triple: [Judicial branch of Nuevo León, partOf, Government of Nuevo León]
Generated description
The Government of Nuevo León is the state-level governing authority of Nuevo León, Mexico, encompassing its executive, legislative, and judicial branches.

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_69ef6a50d8088190acbf3dfbb06d8091 completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f6380636408190ad8ce010a00b837b completed May 2, 2026, 5:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12ecca77008190a67283aa1ad74d5a completed May 24, 2026, 12:19 p.m.
NEDg Description generation batch_6a12ee6cf0248190baa47c6c3b1d0da0 completed May 24, 2026, 12:26 p.m.
NED2 Entity disambiguation (via description) batch_6a12eed1969c8190863ee5504ec3659b completed May 24, 2026, 12:28 p.m.
Created at: April 27, 2026, 5:27 p.m.