Triple

T1016273
Position Surface form Disambiguated ID Type / Status
Subject Verna Fields E21937 entity
Predicate familyName P18 FINISHED
Object Fields
Fields is a common English surname borne by numerous notable individuals across diverse fields such as entertainment, sports, and academia.
 E121550 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: Fields | Statement: [Verna Fields, familyName, Fields]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fields
Context triple: [Verna Fields, familyName, Fields]
  • A. Field
    Field is a common English surname borne by numerous notable individuals across business, politics, sports, and the arts.
  • B. Regions Field
    Regions Field is a modern minor league baseball stadium in Birmingham, Alabama, serving as the home of the Birmingham Barons.
  • C. Fields Corner
    Fields Corner is a rapid transit station in Dorchester, Boston, serving as a key stop on the Massachusetts Bay Transportation Authority’s Red Line.
  • D. Sandfields
    Sandfields is a coastal residential and industrial area within the county borough of Neath Port Talbot in South Wales.
  • E. Meadows
    Meadows is a surname most prominently associated with Mark Meadows, a former White House Chief of Staff and U.S. congressman.
  • 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: Fields
Triple: [Verna Fields, familyName, Fields]
Generated description
Fields is a common English surname borne by numerous notable individuals across diverse fields such as entertainment, sports, and academia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fields
Target entity description: Fields is a common English surname borne by numerous notable individuals across diverse fields such as entertainment, sports, and academia.
  • A. Field
    Field is a common English surname borne by numerous notable individuals across business, politics, sports, and the arts.
  • B. Regions Field
    Regions Field is a modern minor league baseball stadium in Birmingham, Alabama, serving as the home of the Birmingham Barons.
  • C. Fields Corner
    Fields Corner is a rapid transit station in Dorchester, Boston, serving as a key stop on the Massachusetts Bay Transportation Authority’s Red Line.
  • D. Sandfields
    Sandfields is a coastal residential and industrial area within the county borough of Neath Port Talbot in South Wales.
  • E. Meadows
    Meadows is a surname most prominently associated with Mark Meadows, a former White House Chief of Staff and U.S. congressman.
  • 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_69a493c68e24819080ed0ee8bcfd5ce0 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b7c1e9d08190baf7e81f3777168d completed March 1, 2026, 10:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3bb1b0bc819095af3b50bfebca1e completed March 7, 2026, 2:52 p.m.
NEDg Description generation batch_69ac3dd441fc8190ad462aa07e9c8c9b completed March 7, 2026, 3:01 p.m.
NED2 Entity disambiguation (via description) batch_69ac3e45d9e88190bc88d037c00c3ecc completed March 7, 2026, 3:03 p.m.
Created at: March 1, 2026, 7:41 p.m.