Triple

T36788943
Position Surface form Disambiguated ID Type / Status
Subject Witches of East End E908998 entity
Predicate executiveProducer P7225 FINISHED
Object Debra Fisher
Debra Fisher is a television producer and writer best known for her work as an executive producer on the supernatural drama series "Witches of East End."
E2211711 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: Debra Fisher | Statement: [Witches of East End, executiveProducer, Debra Fisher]
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: Debra Fisher
Triple: [Witches of East End, executiveProducer, Debra Fisher]
Generated description
Debra Fisher is a television producer and writer best known for her work as an executive producer on the supernatural drama series "Witches of East End."

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_69f76e7a937c81909ed7359641e670f6 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c9fcc1908190b2d1274de9fad808 completed May 3, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3efda3d6b08190bff513454663f404 completed June 26, 2026, 10:31 p.m.
NEDg Description generation batch_6a3efe9eb99c8190ab72ef6c66f6b7b5 completed June 26, 2026, 10:35 p.m.
NED2 Entity disambiguation (via description) batch_6a3efef25954819093ef7778c49d491a completed June 26, 2026, 10:36 p.m.
Created at: May 3, 2026, 4:12 p.m.