Triple

T26724671
Position Surface form Disambiguated ID Type / Status
Subject English translation of Primo Levi’s "Other People’s Trades" E673803 entity
Predicate title P38 FINISHED
Object Other People’s Trades
Other People’s Trades is an essay collection by Primo Levi that reflects on science, literature, and everyday life with his characteristic clarity and humanism.
E1738442 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: Other People’s Trades | Statement: [English translation of Primo Levi’s "Other People’s Trades", title, Other People’s Trades]
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: Other People’s Trades
Triple: [English translation of Primo Levi’s "Other People’s Trades", title, Other People’s Trades]
Generated description
Other People’s Trades is an essay collection by Primo Levi that reflects on science, literature, and everyday life with his characteristic clarity and humanism.

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_69eecda481d08190aea69f2f7c745f56 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f6180905dc819090453de138391b2c completed May 2, 2026, 3:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11fe942bc481908b745925c7cbad82 completed May 23, 2026, 7:23 p.m.
NEDg Description generation batch_6a11ff67f7748190ad1c6874be3660e1 completed May 23, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_6a11fffd6b1081909ed36e05ffdaed73 completed May 23, 2026, 7:29 p.m.
Created at: April 27, 2026, 3:42 a.m.