Triple

T36362595
Position Surface form Disambiguated ID Type / Status
Subject If Anything Happens I Love You E895534 entity
Predicate awardReceived P11 FINISHED
Object AFI Fest Special Jury Prize
The AFI Fest Special Jury Prize is an award presented at the AFI Fest film festival to recognize outstanding achievement in filmmaking as selected by a festival jury.
E2180296 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: AFI Fest Special Jury Prize | Statement: [If Anything Happens I Love You, awardReceived, AFI Fest Special Jury Prize]
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: AFI Fest Special Jury Prize
Triple: [If Anything Happens I Love You, awardReceived, AFI Fest Special Jury Prize]
Generated description
The AFI Fest Special Jury Prize is an award presented at the AFI Fest film festival to recognize outstanding achievement in filmmaking as selected by a festival jury.

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_69f76e5044248190b390d8887dc03254 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bacb7a70819083e74d2cfa28cf36 completed May 3, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39a331eeb4819093ec8915b0bb47ac completed June 22, 2026, 9:03 p.m.
NEDg Description generation batch_6a39a72b9a148190b83e1ecbadb0f8ab completed June 22, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a39a7dc5c708190b35914ed21dead24 completed June 22, 2026, 9:23 p.m.
Created at: May 3, 2026, 4:10 p.m.