Triple

T32314270
Position Surface form Disambiguated ID Type / Status
Subject Jan Němec E825586 entity
Predicate notableWork P4 FINISHED
Object Late Night Talks with Mother
Late Night Talks with Mother is a 2001 Czech film by director Jan Němec that blends autobiographical reflection and experimental storytelling through imagined conversations with his deceased mother.
 E2002503 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: Late Night Talks with Mother | Statement: [Jan Němec, notableWork, Late Night Talks with Mother]
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: Late Night Talks with Mother
Triple: [Jan Němec, notableWork, Late Night Talks with Mother]
Generated description
Late Night Talks with Mother is a 2001 Czech film by director Jan Němec that blends autobiographical reflection and experimental storytelling through imagined conversations with his deceased mother.

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_69f3491213b88190a57094d8697a7455 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bdb9771c81909894f0efa4f05a89 completed May 3, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a305719d51c8190872a5aead111c1d3 completed June 15, 2026, 7:48 p.m.
NEDg Description generation batch_6a31b25563188190a03c27ce33657b96 completed June 16, 2026, 8:30 p.m.
NED2 Entity disambiguation (via description) batch_6a31b603baf88190b24834df8d6ab728 completed June 16, 2026, 8:45 p.m.
Created at: May 1, 2026, 12:46 a.m.