Triple

T29002732
Position Surface form Disambiguated ID Type / Status
Subject Scott Weiland E736346 entity
Predicate spouse P13 FINISHED
Object Mary Forsberg
Mary Forsberg is an American model and author best known for her long-term relationship and marriage to late Stone Temple Pilots frontman Scott Weiland and for her memoir detailing her experiences with addiction and mental health.
E1847835 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: Mary Forsberg | Statement: [Scott Weiland, spouse, Mary Forsberg]
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: Mary Forsberg
Triple: [Scott Weiland, spouse, Mary Forsberg]
Generated description
Mary Forsberg is an American model and author best known for her long-term relationship and marriage to late Stone Temple Pilots frontman Scott Weiland and for her memoir detailing her experiences with addiction and mental health.

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_69f077eb81e88190ad9ff62cbb9f555e completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f65fbd59d0819095a6bfb40c7c96d5 completed May 2, 2026, 8:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a251f63a6d48190a512552e8f1bce80 completed June 7, 2026, 7:36 a.m.
NEDg Description generation batch_6a2523ec5098819093f3576fd35f335d completed June 7, 2026, 7:55 a.m.
NED2 Entity disambiguation (via description) batch_6a2527e117c88190989c7965f5d99f87 completed June 7, 2026, 8:12 a.m.
Created at: April 28, 2026, 9:36 a.m.