Triple

T31323956
Position Surface form Disambiguated ID Type / Status
Subject Batman: Hush E798828 entity
Predicate editor P1954 FINISHED
Object Bob Schreck
Bob Schreck is an American comic book editor and publisher known for his influential work at DC Comics, Dark Horse, and Oni Press, where he helped shape major titles and support prominent creators.
E1958454 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: Bob Schreck | Statement: [Batman: Hush, editor, Bob Schreck]
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: Bob Schreck
Triple: [Batman: Hush, editor, Bob Schreck]
Generated description
Bob Schreck is an American comic book editor and publisher known for his influential work at DC Comics, Dark Horse, and Oni Press, where he helped shape major titles and support prominent creators.

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_69f224e3238c8190b2291f50ea4962cd completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69eaf30108190b4be087ae9aef2d3 completed May 3, 2026, 1:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2a720d100c8190b74f17e6cf272013 completed June 11, 2026, 8:30 a.m.
NEDg Description generation batch_6a2a7428635c8190895641dd5f7a55ad completed June 11, 2026, 8:39 a.m.
NED2 Entity disambiguation (via description) batch_6a2a8e84f5c081908c01c1229c2a3615 completed June 11, 2026, 10:31 a.m.
Created at: April 29, 2026, 9:15 p.m.