Triple

T31649488
Position Surface form Disambiguated ID Type / Status
Subject Top Cow Productions E807677 entity
Predicate publishes P80 FINISHED
Object The Darkness
The Darkness is a supernatural horror comic book series centered on a mob hitman who inherits a powerful, malevolent force that grants him dark, otherworldly abilities.
E1974698 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: The Darkness | Statement: [Top Cow Productions, publishes, The Darkness]
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: The Darkness
Triple: [Top Cow Productions, publishes, The Darkness]
Generated description
The Darkness is a supernatural horror comic book series centered on a mob hitman who inherits a powerful, malevolent force that grants him dark, otherworldly abilities.

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_69f348d9ce58819093ea2da83cbeeec1 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a95865088190b6c1649a11651edb completed May 3, 2026, 1:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b84aee7dc8190a67f6421c35d8136 completed June 12, 2026, 4:01 a.m.
NEDg Description generation batch_6a2b8987cdf48190a523d9495ddb05ed completed June 12, 2026, 4:22 a.m.
NED2 Entity disambiguation (via description) batch_6a2b8a4c8dac8190b802007e36d7cbf7 completed June 12, 2026, 4:25 a.m.
Created at: April 30, 2026, 10:52 p.m.