Triple

T34185923
Position Surface form Disambiguated ID Type / Status
Subject José Alencar E876958 entity
Predicate honorificTitle P2097 FINISHED
Object Vice President José Alencar
Vice President José Alencar was a Brazilian businessman and politician who served as vice president under President Luiz Inácio Lula da Silva in the 2000s.
E2084803 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: Vice President José Alencar | Statement: [José Alencar, honorificTitle, Vice President José Alencar]
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: Vice President José Alencar
Triple: [José Alencar, honorificTitle, Vice President José Alencar]
Generated description
Vice President José Alencar was a Brazilian businessman and politician who served as vice president under President Luiz Inácio Lula da Silva in the 2000s.

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_69f349ae640c8190b9cd220b5368d8b6 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f710097c608190b55b8c869bf1a131 completed May 3, 2026, 9:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36c1e3d0048190b4f989b1e17bcec0 completed June 20, 2026, 4:37 p.m.
NEDg Description generation batch_6a36c27a91288190bf70c5526c0e9354 completed June 20, 2026, 4:40 p.m.
NED2 Entity disambiguation (via description) batch_6a36c332a3a48190b0bfab6d38ef019a completed June 20, 2026, 4:43 p.m.
Created at: May 1, 2026, 1:55 a.m.