Triple

T28969294
Position Surface form Disambiguated ID Type / Status
Subject The Thanos Quest #1 E734226 entity
Predicate inker P36861 FINISHED
Object John Beatty
John Beatty is an American comic book artist best known as a prolific inker for major publishers like Marvel and DC Comics.
E1857395 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: John Beatty | Statement: [The Thanos Quest #1, inker, John Beatty]
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: John Beatty
Triple: [The Thanos Quest #1, inker, John Beatty]
Generated description
John Beatty is an American comic book artist best known as a prolific inker for major publishers like Marvel and DC 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_69f05b0d1e7c819092baab93d3fe277e completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65c3001908190a21cfe2d25c319eb completed May 2, 2026, 8:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25699b60f48190ae9f078545d8ebef completed June 7, 2026, 12:52 p.m.
NEDg Description generation batch_6a256e06900c81909d7a088c56159bd2 completed June 7, 2026, 1:11 p.m.
NED2 Entity disambiguation (via description) batch_6a25791ab7f08190ae6dd113adf806f1 completed June 7, 2026, 1:58 p.m.
Created at: April 28, 2026, 9:04 a.m.