Triple

T25009796
Position Surface form Disambiguated ID Type / Status
Subject Madame X (1929 film) E625948 entity
Predicate stars P1956 FINISHED
Object Ulrich Haupt
Ulrich Haupt was a German actor active in the early 20th century, known for his roles in silent and early sound films.
E2285270 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: Ulrich Haupt | Statement: [Madame X (1929 film), stars, Ulrich Haupt]
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: Ulrich Haupt
Triple: [Madame X (1929 film), stars, Ulrich Haupt]
Generated description
Ulrich Haupt was a German actor active in the early 20th century, known for his roles in silent and early sound films.

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_69e2ff27755881908490178e83701160 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44b1496ac81909a894f774e8472c9 completed May 1, 2026, 6:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a45cf688c088190801df740f369e0ec completed July 2, 2026, 2:39 a.m.
NEDg Description generation batch_6a45d04d8f448190b3b27934171abec7 completed July 2, 2026, 2:43 a.m.
NED2 Entity disambiguation (via description) batch_6a45d0afa7bc81908a95dedcf187f741 completed July 2, 2026, 2:45 a.m.
Created at: April 18, 2026, 6:05 a.m.