Triple

T32487567
Position Surface form Disambiguated ID Type / Status
Subject Cabinet of Iran E830284 entity
Predicate hasMinisterialPost P7410 FINISHED
Object Minister of Energy of Iran
The Minister of Energy of Iran is the government official responsible for overseeing the country’s energy policies, including electricity generation, water resources, and energy infrastructure development.
E1807774 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: Minister of Energy of Iran | Statement: [Cabinet of Iran, hasMinisterialPost, Minister of Energy of Iran]
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: Minister of Energy of Iran
Triple: [Cabinet of Iran, hasMinisterialPost, Minister of Energy of Iran]
Generated description
The Minister of Energy of Iran is the government official responsible for overseeing the country’s energy policies, including electricity generation, water resources, and energy infrastructure development.

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_69f34920aa4081908d8fb0277414b911 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c3f9344c8190b18188da2feef2d8 completed May 3, 2026, 3:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3470545cf8819089b7d080b61a47fc completed June 18, 2026, 10:25 p.m.
NEDg Description generation batch_6a34710734988190a0a6880097a6a639 completed June 18, 2026, 10:28 p.m.
NED2 Entity disambiguation (via description) batch_6a3471d84d708190bd56542c6f09ba30 completed June 18, 2026, 10:31 p.m.
Created at: May 1, 2026, 12:58 a.m.