Triple

T38611932
Position Surface form Disambiguated ID Type / Status
Subject Ministry of Development and Social Inclusion of Peru E934504 entity
Predicate shortName P43 FINISHED
Object MIDIS
MIDIS is Peru’s Ministry of Development and Social Inclusion, the government body responsible for designing and implementing policies and programs to reduce poverty and promote social inclusion nationwide.
E2277959 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: MIDIS | Statement: [Ministry of Development and Social Inclusion of Peru, shortName, MIDIS]
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: MIDIS
Triple: [Ministry of Development and Social Inclusion of Peru, shortName, MIDIS]
Generated description
MIDIS is Peru’s Ministry of Development and Social Inclusion, the government body responsible for designing and implementing policies and programs to reduce poverty and promote social inclusion nationwide.

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_69f76eccd6d081909ccce171011739a1 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd971a5d881908b25574549e961b8 completed May 7, 2026, 6:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41f4436a008190b2bd9922aa02d3a4 completed June 29, 2026, 4:27 a.m.
NEDg Description generation batch_6a41f55d6f74819085b208204dcd68dc completed June 29, 2026, 4:32 a.m.
NED2 Entity disambiguation (via description) batch_6a41f61ba5a08190b74a5c3ec29c3665 completed June 29, 2026, 4:35 a.m.
Created at: May 3, 2026, 4:32 p.m.