Triple

T11845598
Position Surface form Disambiguated ID Type / Status
Subject Finlandia University E281765 entity
Predicate city P40 FINISHED
Object Hancock
Hancock is a small city in Michigan’s Upper Peninsula known for its Finnish-American heritage and proximity to Lake Superior.
 E949312 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: Hancock | Statement: [Finlandia University, city, Hancock]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hancock
Context triple: [Finlandia University, city, Hancock]
  • A. Hancock
    Hancock is a prominent surname most famously associated with John Hancock, a key figure of the American Revolution and first signer of the United States Declaration of Independence.
  • B. Hancock
    Hancock is a small rural town in western Massachusetts known for its scenic Berkshire landscapes and outdoor recreation.
  • C. Hancock (film)
    Hancock is a 2008 superhero action-comedy film starring Will Smith as a troubled, alcoholic superhero seeking redemption in modern-day Los Angeles.
  • D. Kingman
    Kingman is a surname most notably associated with Sir John Kingman, a prominent British mathematician and statistician.
  • E. Rushmore
    Rushmore is a 1998 Wes Anderson coming-of-age comedy film starring Jason Schwartzman and Bill Murray, known for its offbeat humor, distinctive visual style, and deadpan performances.
  • 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: Hancock
Triple: [Finlandia University, city, Hancock]
Generated description
Hancock is a small city in Michigan’s Upper Peninsula known for its Finnish-American heritage and proximity to Lake Superior.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hancock
Target entity description: Hancock is a small city in Michigan’s Upper Peninsula known for its Finnish-American heritage and proximity to Lake Superior.
  • A. Hancock
    Hancock is a prominent surname most famously associated with John Hancock, a key figure of the American Revolution and first signer of the United States Declaration of Independence.
  • B. Hancock
    Hancock is a small rural town in western Massachusetts known for its scenic Berkshire landscapes and outdoor recreation.
  • C. Hancock (film)
    Hancock is a 2008 superhero action-comedy film starring Will Smith as a troubled, alcoholic superhero seeking redemption in modern-day Los Angeles.
  • D. Kingman
    Kingman is a surname most notably associated with Sir John Kingman, a prominent British mathematician and statistician.
  • E. Rushmore
    Rushmore is a 1998 Wes Anderson coming-of-age comedy film starring Jason Schwartzman and Bill Murray, known for its offbeat humor, distinctive visual style, and deadpan performances.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a65b5ff08190bb58361f6a6acdca completed April 10, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69f167a876048190aeeeccebae9e46ad completed April 29, 2026, 2:06 a.m.
NEDg Description generation batch_69f17005c318819090e54bc64d135477 completed April 29, 2026, 2:42 a.m.
NED2 Entity disambiguation (via description) batch_69f17814de1881908973af026af5d1d1 completed April 29, 2026, 3:16 a.m.
Created at: April 8, 2026, 9:43 p.m.