Triple

T21836103
Position Surface form Disambiguated ID Type / Status
Subject The Milagro Beanfield War E539123 entity
Predicate screenwriter P2831 FINISHED
Object John K. Nichols
John K. Nichols is an American novelist and screenwriter best known for writing the novel and co-writing the film adaptation of "The Milagro Beanfield War."
E2284980 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: John K. Nichols | Statement: [The Milagro Beanfield War, screenwriter, John K. Nichols]
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: John K. Nichols
Triple: [The Milagro Beanfield War, screenwriter, John K. Nichols]
Generated description
John K. Nichols is an American novelist and screenwriter best known for writing the novel and co-writing the film adaptation of "The Milagro Beanfield War."

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_69e0c475cda88190987d08f23caebdc1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0a7a7c368819094e0c4548be30798 completed April 28, 2026, 12:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a44b3916758819092544ab28c7b5afa completed July 1, 2026, 6:28 a.m.
NEDg Description generation batch_6a44b587c3ec8190997b70be1d8c7c15 completed July 1, 2026, 6:36 a.m.
NED2 Entity disambiguation (via description) batch_6a44b5e52690819086e95e560158612c completed July 1, 2026, 6:38 a.m.
Created at: April 16, 2026, 6:55 p.m.