Triple

T24973255
Position Surface form Disambiguated ID Type / Status
Subject Max Fleischer E624947 entity
Predicate relative P37 FINISHED
Object Dave Fleischer
Dave Fleischer was an American film director and producer best known for co-founding Fleischer Studios and co-creating classic animated characters such as Betty Boop and Popeye cartoons.
E1661023 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: Dave Fleischer | Statement: [Max Fleischer, relative, Dave Fleischer]
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: Dave Fleischer
Triple: [Max Fleischer, relative, Dave Fleischer]
Generated description
Dave Fleischer was an American film director and producer best known for co-founding Fleischer Studios and co-creating classic animated characters such as Betty Boop and Popeye cartoons.

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_69e2ff24512481908e9a72315b8d0354 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f444de84408190b69cc03c458d6195 completed May 1, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1048a55b5081909691590148f8154f completed May 22, 2026, 12:14 p.m.
NEDg Description generation batch_6a10498ee91081909f400a590f3646a7 completed May 22, 2026, 12:18 p.m.
NED2 Entity disambiguation (via description) batch_6a104a7bba188190b4d819ed6c618086 completed May 22, 2026, 12:22 p.m.
Created at: April 18, 2026, 6:01 a.m.