Triple

T23739296
Position Surface form Disambiguated ID Type / Status
Subject Sally Field as Dr. Greta Mantleray E586626 entity
Predicate characterName P36851 FINISHED
Object Dr. Greta Mantleray
Dr. Greta Mantleray is a fictional therapist and scientist character from the Netflix miniseries "Maniac," portrayed by Sally Field.
E1602632 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: Dr. Greta Mantleray | Statement: [Sally Field as Dr. Greta Mantleray, characterName, Dr. Greta Mantleray]
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: Dr. Greta Mantleray
Triple: [Sally Field as Dr. Greta Mantleray, characterName, Dr. Greta Mantleray]
Generated description
Dr. Greta Mantleray is a fictional therapist and scientist character from the Netflix miniseries "Maniac," portrayed by Sally Field.

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_69e24908efb08190bf755c3a9b91f222 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1bad427f081908eaf96273fec757b completed April 29, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f53cb76148190be086398d09ca4cc completed May 21, 2026, 6:49 p.m.
NEDg Description generation batch_6a0f58183454819094b938a6809c513a completed May 21, 2026, 7:08 p.m.
NED2 Entity disambiguation (via description) batch_6a0f58be2c44819085064c63d07e6906 completed May 21, 2026, 7:10 p.m.
Created at: April 17, 2026, 7:11 p.m.