Triple

T23987950
Position Surface form Disambiguated ID Type / Status
Subject Bicycle Thieves E604986 entity
Predicate character P662 FINISHED
Object Antonio Ricci
Antonio Ricci is the impoverished Roman father at the heart of Vittorio De Sica’s neorealist film "Bicycle Thieves," whose desperate search for his stolen bicycle drives the story’s emotional and social drama.
E2292408 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: Antonio Ricci | Statement: [Bicycle Thieves, character, Antonio Ricci]
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: Antonio Ricci
Triple: [Bicycle Thieves, character, Antonio Ricci]
Generated description
Antonio Ricci is the impoverished Roman father at the heart of Vittorio De Sica’s neorealist film "Bicycle Thieves," whose desperate search for his stolen bicycle drives the story’s emotional and social drama.

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_69e295463f7c8190b1c19dbd114641b9 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d38902fc8190af51cedfce1c6c13 completed April 29, 2026, 9:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a6885a3140c819081db6c5f54f1c028 completed July 28, 2026, 10:34 a.m.
NEDg Description generation batch_6a68868437b88190be8282151e177e2f completed July 28, 2026, 10:37 a.m.
NED2 Entity disambiguation (via description) batch_6a688736bc0081909c07bb3eb0e4bb5a completed July 28, 2026, 10:40 a.m.
Created at: April 17, 2026, 9:36 p.m.