Triple

T36727415
Position Surface form Disambiguated ID Type / Status
Subject Plaza Matriz E907232 entity
Predicate hasAlternativeName P39 FINISHED
Object Plaza de la Constitución
Plaza de la Constitución is a historic central square in Montevideo, Uruguay, known for its colonial architecture, cathedral, and role as a focal point of civic and social life.
E2210174 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: Plaza de la Constitución | Statement: [Plaza Matriz, hasAlternativeName, Plaza de la Constitución]
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: Plaza de la Constitución
Triple: [Plaza Matriz, hasAlternativeName, Plaza de la Constitución]
Generated description
Plaza de la Constitución is a historic central square in Montevideo, Uruguay, known for its colonial architecture, cathedral, and role as a focal point of civic and social life.

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_69f76e746e4c8190a0d05cc6d57a643e completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c8a195ac8190a7307cff252cab9e completed May 3, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e8c1bbe9c81909261e9c288da73c0 completed June 26, 2026, 2:26 p.m.
NEDg Description generation batch_6a3e9bc7edd48190822561cc620b4e6b completed June 26, 2026, 3:33 p.m.
NED2 Entity disambiguation (via description) batch_6a3ea0e383e081909dbc3c557aae2054 completed June 26, 2026, 3:55 p.m.
Created at: May 3, 2026, 4:12 p.m.