Triple

T36965165
Position Surface form Disambiguated ID Type / Status
Subject Resident Evil comic books E914408 entity
Predicate hasSpinOff P7226 FINISHED
Object Resident Evil: Fire & Ice
Resident Evil: Fire & Ice is a comic book miniseries set in the Resident Evil universe, following a special forces team as they confront bioengineered horrors and corporate conspiracies.
E2250390 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: Fire & Ice | Statement: [Resident Evil comic books, hasSpinOff, Resident Evil: Fire & Ice]
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: Fire & Ice
Triple: [Resident Evil comic books, hasSpinOff, Resident Evil: Fire & Ice]
Generated description
Resident Evil: Fire & Ice is a comic book miniseries set in the Resident Evil universe, following a special forces team as they confront bioengineered horrors and corporate conspiracies.

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_69f76e8c498c8190b2842db80aea8b3b completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9ff2ff7a8819092ebe72ea0c5d3ea completed May 5, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4117d130f881909f9272757de678fb completed June 28, 2026, 12:47 p.m.
NEDg Description generation batch_6a4118db6bfc8190827969ae9f6ca62b completed June 28, 2026, 12:51 p.m.
NED2 Entity disambiguation (via description) batch_6a412489986c8190b86728ae7f1d1c06 completed June 28, 2026, 1:41 p.m.
Created at: May 3, 2026, 4:14 p.m.