Triple

T36361393
Position Surface form Disambiguated ID Type / Status
Subject Close to Home E895501 entity
Predicate creator P184 FINISHED
Object Jim Leonard
Jim Leonard is a television writer and producer best known for creating the American crime drama series "Close to Home."
E2181000 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: Jim Leonard | Statement: [Close to Home, creator, Jim Leonard]
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: Jim Leonard
Triple: [Close to Home, creator, Jim Leonard]
Generated description
Jim Leonard is a television writer and producer best known for creating the American crime drama series "Close to Home."

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_69f76e5044248190b390d8887dc03254 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7baca106c8190a275622686aac155 completed May 3, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39a32fef248190a40141d994bc9828 completed June 22, 2026, 9:03 p.m.
NEDg Description generation batch_6a39a6bfded08190a78732e8c831d73a completed June 22, 2026, 9:18 p.m.
NED2 Entity disambiguation (via description) batch_6a39a86eac3c81908eb7c304b86d0d6a completed June 22, 2026, 9:26 p.m.
Created at: May 3, 2026, 4:09 p.m.