Triple

T29484257
Position Surface form Disambiguated ID Type / Status
Subject Institute for Media and Communication Studies (Free University of Berlin) E747876 entity
Predicate affiliatedWith P254 FINISHED
Object Department of Political and Social Sciences (Free University of Berlin)
The Department of Political and Social Sciences at the Free University of Berlin is an academic division that encompasses disciplines such as political science, sociology, and communication studies, and hosts various specialized institutes and research centers.
E749949 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: Department of Political and Social Sciences (Free University of Berlin) | Statement: [Institute for Media and Communication Studies (Free University of Berlin), affiliatedWith, Department of Political and Social Sciences (Free University of Berlin)]
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: Department of Political and Social Sciences (Free University of Berlin)
Triple: [Institute for Media and Communication Studies (Free University of Berlin), affiliatedWith, Department of Political and Social Sciences (Free University of Berlin)]
Generated description
The Department of Political and Social Sciences at the Free University of Berlin is an academic division that encompasses disciplines such as political science, sociology, and communication studies, and hosts various specialized institutes and research centers.

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_69f0bd43ba30819095eb1cfc3adf525c completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66c04cebc819083ae3b4338149347 completed May 2, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a260c14cfec8190a94c8578ed272730 completed June 8, 2026, 12:25 a.m.
NEDg Description generation batch_6a26103b50948190a67b288cf9f474ce completed June 8, 2026, 12:43 a.m.
NED2 Entity disambiguation (via description) batch_6a261bab40048190b31f5b12454bedbf completed June 8, 2026, 1:32 a.m.
Created at: April 28, 2026, 4:06 p.m.