Triple

T29023794
Position Surface form Disambiguated ID Type / Status
Subject Devon Bostick E737529 entity
Predicate characterPortrayed P1507 FINISHED
Object Jasper Jordan
Jasper Jordan is a main character from the post-apocalyptic TV series "The 100," known for his transformation from comic relief to a deeply traumatized and tragic figure.
E1844487 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: Jasper Jordan | Statement: [Devon Bostick, characterPortrayed, Jasper Jordan]
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: Jasper Jordan
Triple: [Devon Bostick, characterPortrayed, Jasper Jordan]
Generated description
Jasper Jordan is a main character from the post-apocalyptic TV series "The 100," known for his transformation from comic relief to a deeply traumatized and tragic figure.

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_69f077ef00fc81909325f084ad37c035 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f66007a5d8819085fcc6651a89a189 completed May 2, 2026, 8:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2505d3527881909ae458b798a8f7fd completed June 7, 2026, 5:46 a.m.
NEDg Description generation batch_6a2509ba31c8819082af4190ac01be51 completed June 7, 2026, 6:03 a.m.
NED2 Entity disambiguation (via description) batch_6a250e23dd70819082500df27b31e03c completed June 7, 2026, 6:22 a.m.
Created at: April 28, 2026, 9:51 a.m.