Triple

T33985792
Position Surface form Disambiguated ID Type / Status
Subject Chloe in the Afternoon E871405 entity
Predicate musicBy P1952 FINISHED
Object Arié Dzierlatka
Arié Dzierlatka is a composer best known for creating the musical score for Éric Rohmer’s film "Chloe in the Afternoon."
E2156287 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: Arié Dzierlatka | Statement: [Chloe in the Afternoon, musicBy, Arié Dzierlatka]
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: Arié Dzierlatka
Triple: [Chloe in the Afternoon, musicBy, Arié Dzierlatka]
Generated description
Arié Dzierlatka is a composer best known for creating the musical score for Éric Rohmer’s film "Chloe in the Afternoon."

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_69f3499e964c8190b674b03f6f791b4b completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f7038e71948190841a1c2851c777f7 completed May 3, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a389144051c8190bbbcb40b78ffd733 completed June 22, 2026, 1:35 a.m.
NEDg Description generation batch_6a389253d4f881909a40e2c14b4a6d4e completed June 22, 2026, 1:39 a.m.
NED2 Entity disambiguation (via description) batch_6a38930372408190a387347aba837518 completed June 22, 2026, 1:42 a.m.
Created at: May 1, 2026, 1:50 a.m.