Triple

T33792967
Position Surface form Disambiguated ID Type / Status
Subject Noreen Nash E865982 entity
Predicate birthName P65 FINISHED
Object Noreen Roth
Noreen Roth is the birth name of Noreen Nash, an American actress known for her film and television roles in the mid-20th century.
E2145248 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: Noreen Roth | Statement: [Noreen Nash, birthName, Noreen Roth]
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: Noreen Roth
Triple: [Noreen Nash, birthName, Noreen Roth]
Generated description
Noreen Roth is the birth name of Noreen Nash, an American actress known for her film and television roles in the mid-20th century.

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_69f3498f99f481909cb271f4965a7594 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6ff3f5d288190b9280c5801581fc4 completed May 3, 2026, 7:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3852cbf92881909d6e3ba5e0881e63 completed June 21, 2026, 9:08 p.m.
NEDg Description generation batch_6a38537cefd48190b5d223a5506b4f2d completed June 21, 2026, 9:11 p.m.
NED2 Entity disambiguation (via description) batch_6a38546765988190bba6f0bc046274df completed June 21, 2026, 9:15 p.m.
Created at: May 1, 2026, 1:45 a.m.