Triple

T3739115
Position Surface form Disambiguated ID Type / Status
Subject Dilma Rousseff E79655 entity
Predicate twitterUsername P2943 FINISHED
Object @dilmabr
@dilmabr is the official Twitter account of Dilma Rousseff, the former president of Brazil and prominent Brazilian politician.
 E383911 NE FINISHED

How this triple was built (4 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: @dilmabr | Statement: [Dilma Rousseff, twitterUsername, @dilmabr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: @dilmabr
Context triple: [Dilma Rousseff, twitterUsername, @dilmabr]
  • A. DIL
    DIL is a German research institute specializing in food technology and innovation.
  • B. Dimlî
    Dimlî is a Northwestern Iranian language spoken primarily in eastern Turkey, often considered a major dialect or variety of Zazaki.
  • C. Dimalik
    Dimalik is the indigenous traditional religion of the Dimasa people, encompassing their ancestral deities, rituals, and cosmological beliefs.
  • D. Dijlah
    Dijlah is the Arabic name for the Tigris River, one of the major rivers of Western Asia flowing through Turkey, Syria, and Iraq.
  • E. Dashilar
    Dashilar is one of Beijing’s oldest and most famous commercial neighborhoods, known for its traditional alleyways, historic shops, and preserved Qing-era architecture near Tiananmen Square.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: @dilmabr
Triple: [Dilma Rousseff, twitterUsername, @dilmabr]
Generated description
@dilmabr is the official Twitter account of Dilma Rousseff, the former president of Brazil and prominent Brazilian politician.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: @dilmabr
Target entity description: @dilmabr is the official Twitter account of Dilma Rousseff, the former president of Brazil and prominent Brazilian politician.
  • A. DIL
    DIL is a German research institute specializing in food technology and innovation.
  • B. Dimlî
    Dimlî is a Northwestern Iranian language spoken primarily in eastern Turkey, often considered a major dialect or variety of Zazaki.
  • C. Dimalik
    Dimalik is the indigenous traditional religion of the Dimasa people, encompassing their ancestral deities, rituals, and cosmological beliefs.
  • D. Dijlah
    Dijlah is the Arabic name for the Tigris River, one of the major rivers of Western Asia flowing through Turkey, Syria, and Iraq.
  • E. Dashilar
    Dashilar is one of Beijing’s oldest and most famous commercial neighborhoods, known for its traditional alleyways, historic shops, and preserved Qing-era architecture near Tiananmen Square.
  • F. None of above. chosen

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_69ad8b115610819095b02007da5ca3cb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb404b908190b6b4ee583dee3cc9 completed March 8, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db23ff3c81908d19295a7ce4a39c completed March 14, 2026, 3:51 a.m.
NEDg Description generation batch_69b4dbabb314819092dbd1ece83a894c completed March 14, 2026, 3:53 a.m.
NED2 Entity disambiguation (via description) batch_69b4dc9b80f8819083074657a32798a4 completed March 14, 2026, 3:57 a.m.
Created at: March 8, 2026, 3:34 p.m.