Triple

T19308752
Position Surface form Disambiguated ID Type / Status
Subject Genesis and Development of a Scientific Fact E482909 entity
Predicate translator P5475 FINISHED
Object Thaddeus J. Trenn
Thaddeus J. Trenn was a scholar and translator known for his English translation of Ludwik Fleck’s influential work "Genesis and Development of a Scientific Fact."
E1945804 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: Thaddeus J. Trenn | Statement: [Genesis and Development of a Scientific Fact, translator, Thaddeus J. Trenn]
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: Thaddeus J. Trenn
Triple: [Genesis and Development of a Scientific Fact, translator, Thaddeus J. Trenn]
Generated description
Thaddeus J. Trenn was a scholar and translator known for his English translation of Ludwik Fleck’s influential work "Genesis and Development of a Scientific Fact."

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_69d8e8d04d5c8190baa816986f2b1d1e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e604cb47c88190bd01e6f5f4d2204f completed April 20, 2026, 10:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a292ae605148190936d8e9762c6d2f6 completed June 10, 2026, 9:14 a.m.
NEDg Description generation batch_6a292f17b0d88190a8127db7fef88d4a completed June 10, 2026, 9:32 a.m.
NED2 Entity disambiguation (via description) batch_6a29336ad4a88190913d094aaa393fcf completed June 10, 2026, 9:50 a.m.
Created at: April 10, 2026, 1:32 p.m.