Triple

T30419868
Position Surface form Disambiguated ID Type / Status
Subject James William Troup E773870 entity
Predicate knownAs P39 FINISHED
Object James W. Troup
James W. Troup was a prominent Canadian steamship captain and transportation executive active on the Pacific Northwest’s inland and coastal waterways in the late 19th and early 20th centuries.
E2232698 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: James W. Troup | Statement: [James William Troup, knownAs, James W. Troup]
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: James W. Troup
Triple: [James William Troup, knownAs, James W. Troup]
Generated description
James W. Troup was a prominent Canadian steamship captain and transportation executive active on the Pacific Northwest’s inland and coastal waterways in the late 19th and early 20th centuries.

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_69f22491ba248190b9a4776ca8e42d02 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6864cd7548190b3e12ef2fe253ad8 completed May 2, 2026, 11:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a409ee3103481908ff1859e7ff29f98 completed June 28, 2026, 4:11 a.m.
NEDg Description generation batch_6a40a0bb718081909f6f7d021b52070c completed June 28, 2026, 4:19 a.m.
NED2 Entity disambiguation (via description) batch_6a40a180222c8190aa3f63942e798f2f completed June 28, 2026, 4:22 a.m.
Created at: April 29, 2026, 8:05 p.m.