Triple

T27847714
Position Surface form Disambiguated ID Type / Status
Subject Kraven the Hunter E703868 entity
Predicate alias P39 FINISHED
Object Sergei Kravin
Sergei Kravin, better known as Kraven the Hunter, is a formidable Marvel Comics supervillain and master big-game hunter obsessed with proving himself as Spider-Man’s ultimate adversary.
E2294915 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: Sergei Kravin | Statement: [Kraven the Hunter, alias, Sergei Kravin]
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: Sergei Kravin
Triple: [Kraven the Hunter, alias, Sergei Kravin]
Generated description
Sergei Kravin, better known as Kraven the Hunter, is a formidable Marvel Comics supervillain and master big-game hunter obsessed with proving himself as Spider-Man’s ultimate adversary.

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_69ef840d9e3c819093615ebff4ec22be completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f63902060081909bb490327b0c16f2 completed May 2, 2026, 5:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7c3e7e6a0481908b5acf584483a226 completed Aug. 12, 2026, 9:35 a.m.
NEDg Description generation batch_6a7c3ef1ad748190a493573843ada2e4 completed Aug. 12, 2026, 9:37 a.m.
NED2 Entity disambiguation (via description) batch_6a7c418e60988190918ae07a20554b9a completed Aug. 12, 2026, 9:49 a.m.
Created at: April 27, 2026, 6:08 p.m.