Triple

T9498613
Position Surface form Disambiguated ID Type / Status
Subject Cham E229076 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object CHA
CHA is the vehicle registration code for the city of Cham in Germany.
 E802092 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: CHA | Statement: [Cham, hasVehicleRegistrationCode, CHA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CHA
Context triple: [Cham, hasVehicleRegistrationCode, CHA]
  • A. CHA
    The Charlotte Hornets are a professional basketball team based in Charlotte, North Carolina, competing in the NBA's Eastern Conference.
  • B. CHA
    CHA is the standard abbreviation used for the Chattanooga Lookouts, a Minor League Baseball team based in Chattanooga, Tennessee.
  • C. CHAN
    CHAN is the commonly used acronym for the African Nations Championship, a continental football tournament featuring national teams composed exclusively of players active in their domestic leagues.
  • D. CHE
    CHE is the three-letter ISO 3166-1 alpha-3 country code for Switzerland.
  • E. CHS
    CHS is the abbreviation for the Committee on Hemispheric Security, a body within the Organization of American States focused on security issues in the Western Hemisphere.
  • 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: CHA
Triple: [Cham, hasVehicleRegistrationCode, CHA]
Generated description
CHA is the vehicle registration code for the city of Cham in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CHA
Target entity description: CHA is the vehicle registration code for the city of Cham in Germany.
  • A. CHA
    The Charlotte Hornets are a professional basketball team based in Charlotte, North Carolina, competing in the NBA's Eastern Conference.
  • B. CHA
    CHA is the standard abbreviation used for the Chattanooga Lookouts, a Minor League Baseball team based in Chattanooga, Tennessee.
  • C. CHAN
    CHAN is the commonly used acronym for the African Nations Championship, a continental football tournament featuring national teams composed exclusively of players active in their domestic leagues.
  • D. CHE
    CHE is the three-letter ISO 3166-1 alpha-3 country code for Switzerland.
  • E. CHS
    CHS is the abbreviation for the Committee on Hemispheric Security, a body within the Organization of American States focused on security issues in the Western Hemisphere.
  • 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_69ca84753660819098e8d416e89e26ae completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd95ef06b88190b7a840caddea3e38 completed April 1, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12d3aafb88190ac53289039bca88a completed April 4, 2026, 3:24 p.m.
NEDg Description generation batch_69d12dcae2088190bdb4ebac9021e622 completed April 4, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69d12e4077a4819094e86eb0de69b2ed completed April 4, 2026, 3:29 p.m.
Created at: March 30, 2026, 7:56 p.m.