Triple

T29784359
Position Surface form Disambiguated ID Type / Status
Subject Agustín de Betancourt E756220 entity
Predicate familyName P18 FINISHED
Object de Betancourt
de Betancourt is a Spanish surname historically associated with notable figures in engineering, politics, and colonial administration.
 E1884597 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: de Betancourt | Statement: [Agustín de Betancourt, familyName, de Betancourt]
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: de Betancourt
Triple: [Agustín de Betancourt, familyName, de Betancourt]
Generated description
de Betancourt is a Spanish surname historically associated with notable figures in engineering, politics, and colonial administration.

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_69f22451fb748190bbdbab401280affb completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f674a897c88190a9e671b2a47b57bb completed May 2, 2026, 10:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26c9021c048190b213b404c6f244a8 completed June 8, 2026, 1:52 p.m.
NEDg Description generation batch_6a26cdc691908190b77f414999609fc7 completed June 8, 2026, 2:12 p.m.
NED2 Entity disambiguation (via description) batch_6a26d933b93c8190b44f40bdfc3c954f completed June 8, 2026, 3:01 p.m.
Created at: April 29, 2026, 5:07 p.m.