Triple

T32475609
Position Surface form Disambiguated ID Type / Status
Subject Port Robinson E829964 entity
Predicate crossedBy P416 FINISHED
Object Port Robinson ferry
The Port Robinson ferry is a small cable ferry service in Ontario, Canada, that transports passengers and cyclists across the Welland Canal at the village of Port Robinson.
E2008572 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: Port Robinson ferry | Statement: [Port Robinson, crossedBy, Port Robinson ferry]
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: Port Robinson ferry
Triple: [Port Robinson, crossedBy, Port Robinson ferry]
Generated description
The Port Robinson ferry is a small cable ferry service in Ontario, Canada, that transports passengers and cyclists across the Welland Canal at the village of Port Robinson.

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_69f3491ff3b48190b50a7fa00bb05b1f completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c3913f108190b2e10106534b6392 completed May 3, 2026, 3:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34669baa448190b023d97bde0cee01 completed June 18, 2026, 9:43 p.m.
NEDg Description generation batch_6a346728bd388190a0815d78ea6bd4c1 completed June 18, 2026, 9:46 p.m.
NED2 Entity disambiguation (via description) batch_6a3467df74088190b9d033e1534876c6 completed June 18, 2026, 9:49 p.m.
Created at: May 1, 2026, 12:58 a.m.