Triple

T23604898
Position Surface form Disambiguated ID Type / Status
Subject Little Giants E582862 entity
Predicate mainCharacter P1183 FINISHED
Object Rudy Zolteck
Rudy Zolteck is a lovable, overweight young football player from the family sports comedy film "Little Giants," known for his big heart, humor, and underdog spirit.
E1618675 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: Rudy Zolteck | Statement: [Little Giants, mainCharacter, Rudy Zolteck]
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: Rudy Zolteck
Triple: [Little Giants, mainCharacter, Rudy Zolteck]
Generated description
Rudy Zolteck is a lovable, overweight young football player from the family sports comedy film "Little Giants," known for his big heart, humor, and underdog spirit.

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_69e248faa2788190abb1581742daa6aa completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b0ef32b481909590a1a5853df5d9 completed April 29, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f96236e6c81909f9118aecef106f8 completed May 21, 2026, 11:32 p.m.
NEDg Description generation batch_6a0f9a2e8a6881909357812259ae7ff9 completed May 21, 2026, 11:50 p.m.
NED2 Entity disambiguation (via description) batch_6a0f9ae72a8c81909bd7bdb637d3b8c7 completed May 21, 2026, 11:53 p.m.
Created at: April 17, 2026, 6:44 p.m.