Triple

T35213924
Position Surface form Disambiguated ID Type / Status
Subject Power Universe E1016767 entity
Predicate originatedFrom P409 FINISHED
Object Power
Power is a superhero comic book series created by Brian Michael Bendis and Michael Avon Oeming that follows a pair of homicide detectives who investigate crimes involving superpowered individuals.
E2132841 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: Power | Statement: [Power Universe, originatedFrom, Power]
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: Power
Triple: [Power Universe, originatedFrom, Power]
Generated description
Power is a superhero comic book series created by Brian Michael Bendis and Michael Avon Oeming that follows a pair of homicide detectives who investigate crimes involving superpowered individuals.

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_69f76ddf549c8190869d0af076fd2c28 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78e77008081908a60570721b2e4ea completed May 3, 2026, 6:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a380f9d86c8819086a68b06bb5913b4 completed June 21, 2026, 4:21 p.m.
NEDg Description generation batch_6a38106b8b0081909031870bdf9025a3 completed June 21, 2026, 4:25 p.m.
NED2 Entity disambiguation (via description) batch_6a381171e0d88190bce95a7ed5907c20 completed June 21, 2026, 4:29 p.m.
Created at: May 3, 2026, 4:02 p.m.