Triple

T35007656
Position Surface form Disambiguated ID Type / Status
Subject DC Super Hero Girls E1009855 entity
Predicate partOf P40 FINISHED
Object DC Comics multimedia franchises
DC Comics multimedia franchises are cross-platform entertainment properties that expand DC’s superhero characters and stories across films, television, animation, games, and related media.
E205631 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: DC Comics multimedia franchises | Statement: [DC Super Hero Girls, partOf, DC Comics multimedia franchises]
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: DC Comics multimedia franchises
Triple: [DC Super Hero Girls, partOf, DC Comics multimedia franchises]
Generated description
DC Comics multimedia franchises are cross-platform entertainment properties that expand DC’s superhero characters and stories across films, television, animation, games, and related media.

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_69f76dcb716881909f75e4fd60ab2284 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f784ed6e348190b5145d99ec721872 completed May 3, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37bd1800e081908bff91c63ec91a78 completed June 21, 2026, 10:29 a.m.
NEDg Description generation batch_6a37bda6c4408190a6f09442687dae28 completed June 21, 2026, 10:32 a.m.
NED2 Entity disambiguation (via description) batch_6a37bf374b7081908687f2997935411e completed June 21, 2026, 10:38 a.m.
Created at: May 3, 2026, 4:01 p.m.