Triple

T30422818
Position Surface form Disambiguated ID Type / Status
Subject Shadows of Forgotten Ancestors E773943 entity
Predicate costumeDesignBy P184 FINISHED
Object Lyudmyla Semikina
Lyudmyla Semikina is a Ukrainian costume designer best known for her work on the acclaimed film "Shadows of Forgotten Ancestors."
E2062126 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: Lyudmyla Semikina | Statement: [Shadows of Forgotten Ancestors, costumeDesignBy, Lyudmyla Semikina]
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: Lyudmyla Semikina
Triple: [Shadows of Forgotten Ancestors, costumeDesignBy, Lyudmyla Semikina]
Generated description
Lyudmyla Semikina is a Ukrainian costume designer best known for her work on the acclaimed film "Shadows of Forgotten Ancestors."

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_69f22491ba248190b9a4776ca8e42d02 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6866596e0819096567c2f7c121936 completed May 2, 2026, 11:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3626f8659c8190880f1474bd96f51b completed June 20, 2026, 5:36 a.m.
NEDg Description generation batch_6a36279033e081909b97ac755ae90116 completed June 20, 2026, 5:39 a.m.
NED2 Entity disambiguation (via description) batch_6a362968a6c08190beb1123ec9f3b337 completed June 20, 2026, 5:47 a.m.
Created at: April 29, 2026, 8:06 p.m.