Triple

T33109690
Position Surface form Disambiguated ID Type / Status
Subject Joaquín Balaguer E847294 entity
Predicate notableWork P4 FINISHED
Object La realidad dominicana
La realidad dominicana is a political and sociological essay by Joaquín Balaguer that analyzes the historical, social, and cultural conditions shaping the Dominican Republic.
E2036669 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: La realidad dominicana | Statement: [Joaquín Balaguer, notableWork, La realidad dominicana]
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: La realidad dominicana
Triple: [Joaquín Balaguer, notableWork, La realidad dominicana]
Generated description
La realidad dominicana is a political and sociological essay by Joaquín Balaguer that analyzes the historical, social, and cultural conditions shaping the Dominican Republic.

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_69f3495686508190b76bf20fa5e00bf7 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d6e96b6481908a449b8a4b0f8693 completed May 3, 2026, 5:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34f034d3c48190a38225696325dbac completed June 19, 2026, 7:31 a.m.
NEDg Description generation batch_6a34f51a14ec8190a60c715838742ea9 completed June 19, 2026, 7:51 a.m.
NED2 Entity disambiguation (via description) batch_6a34f59441c08190a306eb2fcfecfe74 completed June 19, 2026, 7:53 a.m.
Created at: May 1, 2026, 1:27 a.m.