Triple

T560617
Position Surface form Disambiguated ID Type / Status
Subject Minneapolis E13441 entity
Predicate nickname P55 FINISHED
Object City of Lakes
City of Lakes is a popular nickname for Minneapolis, highlighting its many urban lakes and waterfronts.
 E71329 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: City of Lakes | Statement: [Minneapolis, nickname, City of Lakes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: City of Lakes
Context triple: [Minneapolis, nickname, City of Lakes]
  • A. Lakeside
    Lakeside is an upscale seafood restaurant at the Wynn Las Vegas known for its lakefront views and fine dining experience.
  • B. Robin Lake Beach
    Robin Lake Beach is a large man-made recreational beach and swimming area within Callaway Gardens in Pine Mountain, Georgia, known for its white sand, water activities, and seasonal events.
  • C. Vails Grove
    Vails Grove is a small hamlet within the Town of Southeast in Putnam County, New York, known primarily as a residential lakeside community.
  • D. Kirkewood
    Kirkewood is an alternative spelling of the name Kirkwood, which is used for various places and surnames in English-speaking regions.
  • E. South Meadows
    South Meadows is a neighborhood in Hartford, Connecticut, known for its mix of industrial areas, commercial development, and riverfront land along the Connecticut River.
  • 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: City of Lakes
Triple: [Minneapolis, nickname, City of Lakes]
Generated description
City of Lakes is a popular nickname for Minneapolis, highlighting its many urban lakes and waterfronts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: City of Lakes
Target entity description: City of Lakes is a popular nickname for Minneapolis, highlighting its many urban lakes and waterfronts.
  • A. Lakeside
    Lakeside is an upscale seafood restaurant at the Wynn Las Vegas known for its lakefront views and fine dining experience.
  • B. Robin Lake Beach
    Robin Lake Beach is a large man-made recreational beach and swimming area within Callaway Gardens in Pine Mountain, Georgia, known for its white sand, water activities, and seasonal events.
  • C. Vails Grove
    Vails Grove is a small hamlet within the Town of Southeast in Putnam County, New York, known primarily as a residential lakeside community.
  • D. Kirkewood
    Kirkewood is an alternative spelling of the name Kirkwood, which is used for various places and surnames in English-speaking regions.
  • E. South Meadows
    South Meadows is a neighborhood in Hartford, Connecticut, known for its mix of industrial areas, commercial development, and riverfront land along the Connecticut River.
  • 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_69a4933edcf08190b35ecfd6014caee6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a499e2795c8190903240e79964156d completed March 1, 2026, 7:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4fc7dea048190a5a1472825f6d747 completed March 2, 2026, 2:57 a.m.
NEDg Description generation batch_69a4fcf4f4048190ae7ec93774c292be completed March 2, 2026, 2:59 a.m.
NED2 Entity disambiguation (via description) batch_69a4fd51f2608190b7835e7ba0d78adb completed March 2, 2026, 3 a.m.
Created at: March 1, 2026, 7:32 p.m.