Triple

T24901760
Position Surface form Disambiguated ID Type / Status
Subject George DiCenzo E623597 entity
Predicate role P268 FINISHED
Object Sam Baines in Back to the Future
Sam Baines in *Back to the Future* is Lorraine Baines’ gruff but good-hearted father and Marty McFly’s future grandfather, who appears in the 1955 scenes of the film.
E1657261 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: Sam Baines in Back to the Future | Statement: [George DiCenzo, role, Sam Baines in Back to the Future]
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: Sam Baines in Back to the Future
Triple: [George DiCenzo, role, Sam Baines in Back to the Future]
Generated description
Sam Baines in *Back to the Future* is Lorraine Baines’ gruff but good-hearted father and Marty McFly’s future grandfather, who appears in the 1955 scenes of the film.

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_69e2fac797cc8190b30d77f4121099ac completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f42367ecbc8190a2c987cb2faa1290 completed May 1, 2026, 3:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1033263a58819087885c25e94299bf completed May 22, 2026, 10:42 a.m.
NEDg Description generation batch_6a10341e764c819083c10e4d151da1c6 completed May 22, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a1034cf890881908bd25523cdb83586 completed May 22, 2026, 10:49 a.m.
Created at: April 18, 2026, 5:27 a.m.