Triple

T32287815
Position Surface form Disambiguated ID Type / Status
Subject Valerie and Her Week of Wonders E824882 entity
Predicate leadActor P1507 FINISHED
Object Jaroslava Schallerová
Jaroslava Schallerová is a Czech actress best known for her starring role in the 1970 surrealist fantasy film "Valerie and Her Week of Wonders."
E2029482 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: Jaroslava Schallerová | Statement: [Valerie and Her Week of Wonders, leadActor, Jaroslava Schallerová]
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: Jaroslava Schallerová
Triple: [Valerie and Her Week of Wonders, leadActor, Jaroslava Schallerová]
Generated description
Jaroslava Schallerová is a Czech actress best known for her starring role in the 1970 surrealist fantasy film "Valerie and Her Week of Wonders."

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_69f349101b788190b4f14884dc7d1ed2 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bd311adc8190839fa2f9bb2e727d completed May 3, 2026, 3:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34d24058c88190bde7a5d2230c3006 completed June 19, 2026, 5:23 a.m.
NEDg Description generation batch_6a34d32a229481909a407bea93892806 completed June 19, 2026, 5:27 a.m.
NED2 Entity disambiguation (via description) batch_6a34d3ab5e98819091f34300bf83621d completed June 19, 2026, 5:29 a.m.
Created at: May 1, 2026, 12:44 a.m.