Triple

T28503081
Position Surface form Disambiguated ID Type / Status
Subject Public Against Violence E721289 entity
Predicate keyFigure P256 FINISHED
Object Fedor Gál
Fedor Gál is a Slovak sociologist, politician, and civic activist best known as a leading figure of the Velvet Revolution and post-communist democratic transformation in Slovakia.
E1824187 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: Fedor Gál | Statement: [Public Against Violence, keyFigure, Fedor Gál]
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: Fedor Gál
Triple: [Public Against Violence, keyFigure, Fedor Gál]
Generated description
Fedor Gál is a Slovak sociologist, politician, and civic activist best known as a leading figure of the Velvet Revolution and post-communist democratic transformation in Slovakia.

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_69f01a5afdac8190ac6e72d5c100bd58 completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f64f461b7881909fc1d31426034bec completed May 2, 2026, 7:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cb6d8bbc08190ab66597e5eb24777 completed May 31, 2026, 10:31 p.m.
NEDg Description generation batch_6a1cb92cead88190abd0ad73c3eb8ce6 completed May 31, 2026, 10:41 p.m.
NED2 Entity disambiguation (via description) batch_6a1cb9c3e8e88190bf5c5955adf18073 completed May 31, 2026, 10:44 p.m.
Created at: April 28, 2026, 3:07 a.m.