Triple

T30533045
Position Surface form Disambiguated ID Type / Status
Subject Leon S. Kennedy E777058 entity
Predicate appearsIn P795 FINISHED
Object Resident Evil: Vendetta
Resident Evil: Vendetta is a 2017 CGI-animated action-horror film set in the Resident Evil universe, following Leon S. Kennedy and other series protagonists as they confront a deadly bioterrorist threat.
E1944513 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: Resident Evil: Vendetta | Statement: [Leon S. Kennedy, appearsIn, Resident Evil: Vendetta]
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: Resident Evil: Vendetta
Triple: [Leon S. Kennedy, appearsIn, Resident Evil: Vendetta]
Generated description
Resident Evil: Vendetta is a 2017 CGI-animated action-horror film set in the Resident Evil universe, following Leon S. Kennedy and other series protagonists as they confront a deadly bioterrorist threat.

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_69f2249c11508190ae7e955755ccfb01 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6884deb64819083f346e9ac4824ba completed May 2, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a292aef68cc8190b715f97b8ceb18d2 completed June 10, 2026, 9:14 a.m.
NEDg Description generation batch_6a292d578eec8190a3b32a1a28ee071d completed June 10, 2026, 9:24 a.m.
NED2 Entity disambiguation (via description) batch_6a292db3dce08190b8b4357e0101d18c completed June 10, 2026, 9:26 a.m.
Created at: April 29, 2026, 8:18 p.m.