Triple

T36697131
Position Surface form Disambiguated ID Type / Status
Subject Mark Bagley E906121 entity
Predicate workedOnSeries P100406 FINISHED
Object Trinity
Trinity is a comic book series illustrated by artist Mark Bagley, known for featuring major DC superheroes in a shared storyline.
E1569334 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: Trinity | Statement: [Mark Bagley, workedOnSeries, Trinity]
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: Trinity
Triple: [Mark Bagley, workedOnSeries, Trinity]
Generated description
Trinity is a comic book series illustrated by artist Mark Bagley, known for featuring major DC superheroes in a shared storyline.

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_69f76e7195c48190b5580c9cfb01e95f completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c7eb20548190a946a7257993b2a8 completed May 3, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3c17227f3c81909806d7ba96ca3467 completed June 24, 2026, 5:42 p.m.
NEDg Description generation batch_6a3c19cc0c2c81909a12ddec74a6ccf0 completed June 24, 2026, 5:54 p.m.
NED2 Entity disambiguation (via description) batch_6a3c576fcfe08190a6457bd81d1659a0 completed June 24, 2026, 10:17 p.m.
Created at: May 3, 2026, 4:12 p.m.