Triple

T30494286
Position Surface form Disambiguated ID Type / Status
Subject Miklós Jancsó E775960 entity
Predicate notableWork P4 FINISHED
Object Red Psalm
Red Psalm is a 1972 Hungarian art film by Miklós Jancsó, renowned for its long takes and stylized depiction of a 19th-century peasant revolt.
E1917967 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: Red Psalm | Statement: [Miklós Jancsó, notableWork, Red Psalm]
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: Red Psalm
Triple: [Miklós Jancsó, notableWork, Red Psalm]
Generated description
Red Psalm is a 1972 Hungarian art film by Miklós Jancsó, renowned for its long takes and stylized depiction of a 19th-century peasant revolt.

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_69f22498c5d481908aaea89e6fab8280 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68777c6b8819086d313042ac89831 completed May 2, 2026, 11:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27ac30c5a88190b4f1a2a7b1ec68aa completed June 9, 2026, 6:01 a.m.
NEDg Description generation batch_6a27b00f46f88190977ade25095d7011 completed June 9, 2026, 6:17 a.m.
NED2 Entity disambiguation (via description) batch_6a27b0de95cc8190b7550ec09c1260e2 completed June 9, 2026, 6:21 a.m.
Created at: April 29, 2026, 8:14 p.m.