Triple

T35820315
Position Surface form Disambiguated ID Type / Status
Subject The Company You Keep (TV series) E1035478 entity
Predicate executiveProducer P7225 FINISHED
Object Lindsay Goffman
Lindsay Goffman is a television producer best known for her executive production work on the drama series "The Company You Keep."
E2177192 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: Lindsay Goffman | Statement: [The Company You Keep (TV series), executiveProducer, Lindsay Goffman]
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: Lindsay Goffman
Triple: [The Company You Keep (TV series), executiveProducer, Lindsay Goffman]
Generated description
Lindsay Goffman is a television producer best known for her executive production work on the drama series "The Company You Keep."

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_69f76e185ffc8190880b3cdf51decd38 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a8fe213881908773a4990299aabe completed May 3, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a396ded7da081909a53c7e0e8ed14d9 completed June 22, 2026, 5:16 p.m.
NEDg Description generation batch_6a3973065c688190a1dff7d14e03e0ff completed June 22, 2026, 5:38 p.m.
NED2 Entity disambiguation (via description) batch_6a3973cfe8448190acf81d3d500740ef completed June 22, 2026, 5:41 p.m.
Created at: May 3, 2026, 4:06 p.m.