Triple

T32346969
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Social Studies, Masaryk University E826487 entity
Predicate hasAbbreviation P43 FINISHED
Object FSS MU
FSS MU is the Faculty of Social Studies at Masaryk University, a Czech academic institution focused on disciplines such as sociology, political science, psychology, and related social sciences.
 E2001527 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: FSS MU | Statement: [Faculty of Social Studies, Masaryk University, hasAbbreviation, FSS MU]
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: FSS MU
Triple: [Faculty of Social Studies, Masaryk University, hasAbbreviation, FSS MU]
Generated description
FSS MU is the Faculty of Social Studies at Masaryk University, a Czech academic institution focused on disciplines such as sociology, political science, psychology, and related social sciences.

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_69f34914dfc48190a390cd0720d9e86f completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6be52a40c8190a98066f81bed2d67 completed May 3, 2026, 3:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3057315f6481908a0e7ac18fbbe4fa completed June 15, 2026, 7:49 p.m.
NEDg Description generation batch_6a30597b9e80819082ff4ce584d4cea9 completed June 15, 2026, 7:58 p.m.
NED2 Entity disambiguation (via description) batch_6a3059f59eac8190b3bc29633d7d8847 completed June 15, 2026, 8 p.m.
Created at: May 1, 2026, 12:48 a.m.