Triple

T13353539
Position Surface form Disambiguated ID Type / Status
Subject Saint John Sea Dogs E318128 entity
Predicate notableAlumni P51 FINISHED
Object Ryan Tesink
Ryan Tesink is a Canadian professional ice hockey forward known for his junior career in the QMJHL and being drafted by the St. Louis Blues in the NHL.
E1035846 NE FINISHED

How this triple was built (4 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: Ryan Tesink | Statement: [Saint John Sea Dogs, notableAlumni, Ryan Tesink]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ryan Tesink
Context triple: [Saint John Sea Dogs, notableAlumni, Ryan Tesink]
  • A. Ryan ten Doeschate
    Ryan ten Doeschate is a former Dutch all-rounder renowned for his prolific limited-overs batting and key role in county cricket, particularly in England.
  • B. Bryan Helmig
    Bryan Helmig is a technology entrepreneur best known as a co-founder of the workflow automation platform Zapier.
  • C. Ryan Dusick
    Ryan Dusick is an American musician best known as the original drummer and a founding member of the pop rock band Maroon 5.
  • D. Jeffrey Endervelt
    Jeffrey Endervelt is best known as the former husband of American actress and singer Polly Bergen.
  • E. J.J. Voskuil
    J.J. Voskuil was a Dutch writer best known for his monumental, autobiographical novel cycle "Het Bureau," which offers a detailed, ironic portrayal of life inside a government research institute.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Ryan Tesink
Triple: [Saint John Sea Dogs, notableAlumni, Ryan Tesink]
Generated description
Ryan Tesink is a Canadian professional ice hockey forward known for his junior career in the QMJHL and being drafted by the St. Louis Blues in the NHL.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ryan Tesink
Target entity description: Ryan Tesink is a Canadian professional ice hockey forward known for his junior career in the QMJHL and being drafted by the St. Louis Blues in the NHL.
  • A. Ryan ten Doeschate
    Ryan ten Doeschate is a former Dutch all-rounder renowned for his prolific limited-overs batting and key role in county cricket, particularly in England.
  • B. Bryan Helmig
    Bryan Helmig is a technology entrepreneur best known as a co-founder of the workflow automation platform Zapier.
  • C. Ryan Dusick
    Ryan Dusick is an American musician best known as the original drummer and a founding member of the pop rock band Maroon 5.
  • D. Jeffrey Endervelt
    Jeffrey Endervelt is best known as the former husband of American actress and singer Polly Bergen.
  • E. J.J. Voskuil
    J.J. Voskuil was a Dutch writer best known for his monumental, autobiographical novel cycle "Het Bureau," which offers a detailed, ironic portrayal of life inside a government research institute.
  • F. None of above. chosen

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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e8d520881908aa23c7102b72b72 completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f49e5548190b14d09daea628e6b completed May 3, 2026, 10:11 a.m.
NEDg Description generation batch_69f721b1a5d88190b9075437c7ab81a5 completed May 3, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_69f72262ede4819095b3dc4c7cd63450 completed May 3, 2026, 10:24 a.m.
Created at: April 9, 2026, 9:32 p.m.