Triple

T32132270
Position Surface form Disambiguated ID Type / Status
Subject Black Lightning (TV series) E820682 entity
Predicate mainCharacter P1183 FINISHED
Object Anissa Pierce
Anissa Pierce is a superheroine in the Arrowverse known as Thunder, the justice-driven, superpowered daughter of Jefferson Pierce in the TV series "Black Lightning."
E1999705 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: Anissa Pierce | Statement: [Black Lightning (TV series), mainCharacter, Anissa Pierce]
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: Anissa Pierce
Triple: [Black Lightning (TV series), mainCharacter, Anissa Pierce]
Generated description
Anissa Pierce is a superheroine in the Arrowverse known as Thunder, the justice-driven, superpowered daughter of Jefferson Pierce in the TV series "Black Lightning."

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_69f349039e0c819091c7a7d322e3f46d completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b9726c848190bd8a36c32c389f2e completed May 3, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f46bd1890819089799969a2a94e03 completed June 15, 2026, 12:26 a.m.
NEDg Description generation batch_6a2f65f6542c8190bd54a1bf64317371 completed June 15, 2026, 2:39 a.m.
NED2 Entity disambiguation (via description) batch_6a2f66670a1081909e6baa6e4cd8cc71 completed June 15, 2026, 2:41 a.m.
Created at: May 1, 2026, 12:29 a.m.