Triple

T25364462
Position Surface form Disambiguated ID Type / Status
Subject James White E636060 entity
Predicate screenedInSection P4490 FINISHED
Object NEXT section at Sundance Film Festival
The NEXT section at the Sundance Film Festival is a showcase for bold, innovative, and forward-thinking independent films that often experiment with form, style, and storytelling.
E1674675 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: NEXT section at Sundance Film Festival | Statement: [James White, screenedInSection, NEXT section at Sundance Film Festival]
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: NEXT section at Sundance Film Festival
Triple: [James White, screenedInSection, NEXT section at Sundance Film Festival]
Generated description
The NEXT section at the Sundance Film Festival is a showcase for bold, innovative, and forward-thinking independent films that often experiment with form, style, and storytelling.

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_69e75a9b7cf481909f2dcdfb37d95ca7 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f4a10ce1a8819081abc0012ddfaee7 completed May 1, 2026, 12:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10760393cc8190994843c958e22a85 completed May 22, 2026, 3:28 p.m.
NEDg Description generation batch_6a1076d79eb48190a53ba61685534083 completed May 22, 2026, 3:31 p.m.
NED2 Entity disambiguation (via description) batch_6a1077935d948190b863fda3fdd47965 completed May 22, 2026, 3:34 p.m.
Created at: April 21, 2026, 1:36 p.m.