Triple

T36422951
Position Surface form Disambiguated ID Type / Status
Subject Ministry of Local Government and Community Development (Jamaica) E897212 entity
Predicate hasAbbreviation P43 FINISHED
Object MLGCD
MLGCD is the Jamaican government ministry responsible for overseeing local governance, municipal services, and community development across the country.
E2183581 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: MLGCD | Statement: [Ministry of Local Government and Community Development (Jamaica), hasAbbreviation, MLGCD]
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: MLGCD
Triple: [Ministry of Local Government and Community Development (Jamaica), hasAbbreviation, MLGCD]
Generated description
MLGCD is the Jamaican government ministry responsible for overseeing local governance, municipal services, and community development across the country.

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_69f76e559b10819099d6655a6e14587c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd4a304881908385635dfb812093 completed May 3, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39c40e113c8190b7bdd584fbfc8909 completed June 22, 2026, 11:23 p.m.
NEDg Description generation batch_6a39c5416fc0819080b38a93608bca1c completed June 22, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a39c6ab49d88190aad9e87b48eedbda completed June 22, 2026, 11:35 p.m.
Created at: May 3, 2026, 4:10 p.m.