Triple

T36411356
Position Surface form Disambiguated ID Type / Status
Subject Swing Kids E896887 entity
Predicate screenwriter P2831 FINISHED
Object Jonathan Marc Feldman
Jonathan Marc Feldman is a screenwriter best known for writing the 1993 drama film "Swing Kids," which centers on rebellious youth and swing music in Nazi Germany.
E2185893 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: Jonathan Marc Feldman | Statement: [Swing Kids, screenwriter, Jonathan Marc Feldman]
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: Jonathan Marc Feldman
Triple: [Swing Kids, screenwriter, Jonathan Marc Feldman]
Generated description
Jonathan Marc Feldman is a screenwriter best known for writing the 1993 drama film "Swing Kids," which centers on rebellious youth and swing music in Nazi Germany.

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_69f76e54ce408190849acc3f7758937c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd2f658881909fd16c60f0af12f4 completed May 3, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39cfc1120c8190ab7c2b397f96e0a7 completed June 23, 2026, 12:13 a.m.
NEDg Description generation batch_6a39d2a54e888190b2d5677a01152eec completed June 23, 2026, 12:26 a.m.
NED2 Entity disambiguation (via description) batch_6a39d3fdead881908075c5228cf851d6 completed June 23, 2026, 12:31 a.m.
Created at: May 3, 2026, 4:10 p.m.