Triple

T31239338
Position Surface form Disambiguated ID Type / Status
Subject Sianoa Smit-McPhee E796513 entity
Predicate notableWork P4 FINISHED
Object As the Bell Rings
As the Bell Rings is an Australian teen television series that follows the everyday lives and dramas of high school students, often presented in short, episodic segments.
 E1953875 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: As the Bell Rings | Statement: [Sianoa Smit-McPhee, notableWork, As the Bell Rings]
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: As the Bell Rings
Triple: [Sianoa Smit-McPhee, notableWork, As the Bell Rings]
Generated description
As the Bell Rings is an Australian teen television series that follows the everyday lives and dramas of high school students, often presented in short, episodic segments.

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_69f224db69ac81909a370adad6a7ac7c completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69d24c4108190a1f5141e5ce4e01b completed May 3, 2026, 12:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a296be7deb48190ba2a8827ca17e3af completed June 10, 2026, 1:51 p.m.
NEDg Description generation batch_6a297234cfe0819085c96b0bdd13996d completed June 10, 2026, 2:18 p.m.
NED2 Entity disambiguation (via description) batch_6a299cb8192c8190ba49783bd80bde45 completed June 10, 2026, 5:19 p.m.
Created at: April 29, 2026, 9:11 p.m.