Triple

T38443636
Position Surface form Disambiguated ID Type / Status
Subject SpyBoy E906574 entity
Predicate universe P4832 FINISHED
Object Dark Horse Comics universe
The Dark Horse Comics universe is a shared fictional setting that hosts a wide range of creator-owned and licensed comic book series published by Dark Horse Comics.
E2270362 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: Dark Horse Comics universe | Statement: [SpyBoy, universe, Dark Horse Comics universe]
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: Dark Horse Comics universe
Triple: [SpyBoy, universe, Dark Horse Comics universe]
Generated description
The Dark Horse Comics universe is a shared fictional setting that hosts a wide range of creator-owned and licensed comic book series published by Dark Horse Comics.

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_69f76e72878c8190a692836c8b01b58b completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fccdd7f4e48190b698ba6c38328275 completed May 7, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41c29d99608190a8fb91066aa8af9c completed June 29, 2026, 12:55 a.m.
NEDg Description generation batch_6a41c6859bf0819095f167c444ed92bc completed June 29, 2026, 1:12 a.m.
NED2 Entity disambiguation (via description) batch_6a41c72d3824819092fd95b5d41849e8 completed June 29, 2026, 1:15 a.m.
Created at: May 3, 2026, 4:31 p.m.