Triple

T24741913
Position Surface form Disambiguated ID Type / Status
Subject William Symington E618585 entity
Predicate knownFor P22 FINISHED
Object Charlotte Dundas steamboat
The Charlotte Dundas steamboat was an early steam-powered vessel, often regarded as the world's first practical steamboat used for towing on canals.
E1646740 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: Charlotte Dundas steamboat | Statement: [William Symington, knownFor, Charlotte Dundas steamboat]
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: Charlotte Dundas steamboat
Triple: [William Symington, knownFor, Charlotte Dundas steamboat]
Generated description
The Charlotte Dundas steamboat was an early steam-powered vessel, often regarded as the world's first practical steamboat used for towing on canals.

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_69e2fab8f95c81908bb9e552cf3280c2 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f41056b2c8819085b4ee2509352786 completed May 1, 2026, 2:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101025cb248190a4ad9b967c188d33 completed May 22, 2026, 8:13 a.m.
NEDg Description generation batch_6a10136f4b048190b4664398b5929656 completed May 22, 2026, 8:27 a.m.
NED2 Entity disambiguation (via description) batch_6a10143c5c84819081dd4f953fa9841a completed May 22, 2026, 8:30 a.m.
Created at: April 18, 2026, 4:17 a.m.