Triple

T34562427
Position Surface form Disambiguated ID Type / Status
Subject Lucy Doraine E887380 entity
Predicate notableWork P4 FINISHED
Object Sodom und Gomorrha
Sodom und Gomorrha is a 1922 Austrian silent epic film directed by Michael Curtiz, renowned for its biblical themes, grand scale, and as a major role for actress Lucy Doraine.
E2101738 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: Sodom und Gomorrha | Statement: [Lucy Doraine, notableWork, Sodom und Gomorrha]
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: Sodom und Gomorrha
Triple: [Lucy Doraine, notableWork, Sodom und Gomorrha]
Generated description
Sodom und Gomorrha is a 1922 Austrian silent epic film directed by Michael Curtiz, renowned for its biblical themes, grand scale, and as a major role for actress Lucy Doraine.

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_69f349d0c4d881908dd0950f5eb9ec0a completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f720637214819080c89b45c9c7a00b completed May 3, 2026, 10:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37362840a08190a5339cef226a93c0 completed June 21, 2026, 12:54 a.m.
NEDg Description generation batch_6a3736d2432c819083dc2022f6d5b181 completed June 21, 2026, 12:56 a.m.
NED2 Entity disambiguation (via description) batch_6a37375fecf081908a85fdb46751fc6b completed June 21, 2026, 12:59 a.m.
Created at: May 1, 2026, 2:02 a.m.