Triple

T31020781
Position Surface form Disambiguated ID Type / Status
Subject Plan de Jalapa E790445 entity
Predicate follows P134 FINISHED
Object Plan de Perote
Plan de Perote was a 19th-century Mexican political pronouncement that played a role in the era’s frequent military-led challenges to established governments.
 E1943792 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: Plan de Perote | Statement: [Plan de Jalapa, follows, Plan de Perote]
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: Plan de Perote
Triple: [Plan de Jalapa, follows, Plan de Perote]
Generated description
Plan de Perote was a 19th-century Mexican political pronouncement that played a role in the era’s frequent military-led challenges to established governments.

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_69f224c811508190a7de096a5b1f5798 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6948e8e1c8190b5a52facd5422252 completed May 3, 2026, 12:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a29184242448190a64b1b006180ff04 completed June 10, 2026, 7:54 a.m.
NEDg Description generation batch_6a291c3f0ac48190ad53bb321815d82a completed June 10, 2026, 8:11 a.m.
NED2 Entity disambiguation (via description) batch_6a29202910a48190957c7b3a0a18a32a completed June 10, 2026, 8:28 a.m.
Created at: April 29, 2026, 8:58 p.m.