Triple

T32543413
Position Surface form Disambiguated ID Type / Status
Subject Betsy Brandt E831777 entity
Predicate spouse P13 FINISHED
Object Grady Olsen
Grady Olsen is the husband of American actress Betsy Brandt, known for her role as Marie Schrader on the television series "Breaking Bad."
E2010384 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: Grady Olsen | Statement: [Betsy Brandt, spouse, Grady Olsen]
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: Grady Olsen
Triple: [Betsy Brandt, spouse, Grady Olsen]
Generated description
Grady Olsen is the husband of American actress Betsy Brandt, known for her role as Marie Schrader on the television series "Breaking Bad."

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_69f34925fd08819084cfe4ec566cb704 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c57fc940819086d7ab256f2cad71 completed May 3, 2026, 3:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34707cc8208190b208467eda11a530 completed June 18, 2026, 10:26 p.m.
NEDg Description generation batch_6a3471e541888190b41a9562c7d29278 completed June 18, 2026, 10:32 p.m.
NED2 Entity disambiguation (via description) batch_6a347293cdf08190bbc8ce521ded677c completed June 18, 2026, 10:34 p.m.
Created at: May 1, 2026, 1:02 a.m.