Triple

T31815147
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth Zott E812112 entity
Predicate partner P1136 FINISHED
Object Calvin Evans
Calvin Evans is a brilliant but reclusive Nobel-caliber chemist in the novel "Lessons in Chemistry," known for his intense intellect and deep relationship with protagonist Elizabeth Zott.
E1977547 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: Calvin Evans | Statement: [Elizabeth Zott, partner, Calvin Evans]
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: Calvin Evans
Triple: [Elizabeth Zott, partner, Calvin Evans]
Generated description
Calvin Evans is a brilliant but reclusive Nobel-caliber chemist in the novel "Lessons in Chemistry," known for his intense intellect and deep relationship with protagonist Elizabeth Zott.

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_69f348e846c081908eb468a0665afd55 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6acfc99148190a0da24b25af60085 completed May 3, 2026, 2:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2d9d7126c08190a5804d0bae7e8a79 completed June 13, 2026, 6:12 p.m.
NEDg Description generation batch_6a2d9ecabad48190b46bc1bab34d8f74 completed June 13, 2026, 6:17 p.m.
NED2 Entity disambiguation (via description) batch_6a2d9f6ddf3c8190b25ed23670cee971 completed June 13, 2026, 6:20 p.m.
Created at: April 30, 2026, 11:44 p.m.