Triple

T34058614
Position Surface form Disambiguated ID Type / Status
Subject Bolsa Família E873431 entity
Predicate administeredBy P86 FINISHED
Object Ministry of Social Development
The Ministry of Social Development is a Brazilian federal government body responsible for designing and implementing social assistance and poverty-reduction policies and programs.
E2079672 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: Ministry of Social Development | Statement: [Bolsa Família, administeredBy, Ministry of Social Development]
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: Ministry of Social Development
Triple: [Bolsa Família, administeredBy, Ministry of Social Development]
Generated description
The Ministry of Social Development is a Brazilian federal government body responsible for designing and implementing social assistance and poverty-reduction policies and programs.

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_69f349a4af208190afa14888f9c9fb9d completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70b972fec8190bdba728067483e09 completed May 3, 2026, 8:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36a0444fb08190ac3f70aad32d8e4d completed June 20, 2026, 2:14 p.m.
NEDg Description generation batch_6a36a17667748190a341c3a95981392b completed June 20, 2026, 2:19 p.m.
NED2 Entity disambiguation (via description) batch_6a36a1fb0e148190baa397ab55e200bb completed June 20, 2026, 2:21 p.m.
Created at: May 1, 2026, 1:52 a.m.