Triple

T27186388
Position Surface form Disambiguated ID Type / Status
Subject Sanford/Pillsbury E683342 entity
Predicate foundedBy P104 FINISHED
Object Sarah Pillsbury
Sarah Pillsbury is an American film producer known for backing acclaimed independent and mainstream films, including the Oscar-winning "River's Edge" and "Desperately Seeking Susan."
E683343 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: Sarah Pillsbury | Statement: [Sanford/Pillsbury, foundedBy, Sarah Pillsbury]
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: Sarah Pillsbury
Triple: [Sanford/Pillsbury, foundedBy, Sarah Pillsbury]
Generated description
Sarah Pillsbury is an American film producer known for backing acclaimed independent and mainstream films, including the Oscar-winning "River's Edge" and "Desperately Seeking Susan."

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_69eefad140408190b8586fdebcf9af46 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f62580d96c8190a958383f732a5b90 completed May 2, 2026, 4:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129c9464e48190a14e458510b9929f completed May 24, 2026, 6:37 a.m.
NEDg Description generation batch_6a129f5cfce08190aea3ad3cf89f02f8 completed May 24, 2026, 6:49 a.m.
NED2 Entity disambiguation (via description) batch_6a12a04575d48190b7bafa51497b0003 completed May 24, 2026, 6:52 a.m.
Created at: April 27, 2026, 9:30 a.m.