Triple

T19140068
Position Surface form Disambiguated ID Type / Status
Subject Chief E468532 entity
Predicate previousWork P9710 FINISHED
Object Carolina
Carolina is a former professional role held by Chief, likely referring to a prior position or affiliation in their career history.
 E1366823 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: Carolina | Statement: [Chief, previousWork, Carolina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Carolina
Context triple: [Chief, previousWork, Carolina]
  • A. Carolina
    Carolina is a common nickname for the University of North Carolina at Chapel Hill, a major public research university known for its strong academics and athletic programs.
  • B. Carolina
    Carolina is a feminine given name of Latin origin, commonly used in various languages as a form of Caroline or Charles.
  • C. Carolina
    "Carolina" is a country music album by American singer-songwriter Eric Church that helped establish his reputation for blending traditional country with rock influences.
  • D. Carolina
    Carolina is a small town in South Africa’s Mpumalanga province, known historically for coal mining and its rural, highveld surroundings.
  • E. Carolina
    Carolina was a major English colony in North America that later split into the separate colonies (and eventual U.S. states) of North Carolina and South Carolina.
  • 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: Carolina
Triple: [Chief, previousWork, Carolina]
Generated description
Carolina is a former professional role held by Chief, likely referring to a prior position or affiliation in their career history.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Carolina
Target entity description: Carolina is a former professional role held by Chief, likely referring to a prior position or affiliation in their career history.
  • A. Carolina
    Carolina is a small town in South Africa’s Mpumalanga province, known historically for coal mining and its rural, highveld surroundings.
  • B. Carolina
    Carolina is a feminine given name of Latin origin, commonly used in various languages as a form of Caroline or Charles.
  • C. Carolina
    Carolina is a major municipality in Puerto Rico, known for its urban character, commercial centers, and proximity to San Juan.
  • D. Carolina
    Carolina is a common nickname for the University of North Carolina at Chapel Hill, a major public research university known for its strong academics and athletic programs.
  • E. Carolina
    Carolina was a major English colony in North America that later split into the separate colonies (and eventual U.S. states) of North Carolina and South Carolina.
  • 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_69d8dd0796a48190b34ce4cd9d3f3be5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e3f094f88190996279d7b548edea completed April 20, 2026, 8:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0705c4b3448190afe800ef2d7040b8 completed May 15, 2026, 11:38 a.m.
NEDg Description generation batch_6a070620f72c8190b54f6c6c69ff365d completed May 15, 2026, 11:40 a.m.
NED2 Entity disambiguation (via description) batch_6a0706af26a8819092a88bc386af0dbe completed May 15, 2026, 11:42 a.m.
Created at: April 10, 2026, 12:05 p.m.