Triple

T3339076
Position Surface form Disambiguated ID Type / Status
Subject Dorset E70212 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object DOR
DOR is the vehicle registration code used on license plates for the English county of Dorset.
 E349057 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: DOR | Statement: [Dorset, hasVehicleRegistrationCode, DOR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DOR
Context triple: [Dorset, hasVehicleRegistrationCode, DOR]
  • A. DOR
    DOR is the standard abbreviation used for the Mexican football club Dorados de Sinaloa.
  • B. DAR
    DAR is the Philippine government agency responsible for implementing agrarian reform and redistributing agricultural land to farmers.
  • C. DHR
    DHR is the stock ticker symbol for Danaher Corporation, a global science and technology company focused on life sciences, diagnostics, and environmental and applied solutions.
  • D. DRO
    DRO is the commonly used acronym for the Division of Regional Operations, an organizational unit that oversees and coordinates activities across multiple geographic regions.
  • E. DOP
    DOP is the common abbreviation for the Daughters of Penelope, a women’s organization affiliated with the American Hellenic Educational Progressive Association that promotes Hellenic ideals, philanthropy, and civic responsibility.
  • 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: DOR
Triple: [Dorset, hasVehicleRegistrationCode, DOR]
Generated description
DOR is the vehicle registration code used on license plates for the English county of Dorset.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DOR
Target entity description: DOR is the vehicle registration code used on license plates for the English county of Dorset.
  • A. DOR
    DOR is the standard abbreviation used for the Mexican football club Dorados de Sinaloa.
  • B. DAR
    DAR is the Philippine government agency responsible for implementing agrarian reform and redistributing agricultural land to farmers.
  • C. DHR
    DHR is the stock ticker symbol for Danaher Corporation, a global science and technology company focused on life sciences, diagnostics, and environmental and applied solutions.
  • D. DRO
    DRO is the commonly used acronym for the Division of Regional Operations, an organizational unit that oversees and coordinates activities across multiple geographic regions.
  • E. DOP
    DOP is the common abbreviation for the Daughters of Penelope, a women’s organization affiliated with the American Hellenic Educational Progressive Association that promotes Hellenic ideals, philanthropy, and civic responsibility.
  • 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_69ad85a405e48190b6e68de7cf9f319e completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1bd6c7c8190b7229de1433d8d20 completed March 8, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a8ccc408190bae65d2d1a4d77bd completed March 12, 2026, 7:57 p.m.
NEDg Description generation batch_69b31aded5808190afbe4ae3ddb70428 completed March 12, 2026, 7:58 p.m.
NED2 Entity disambiguation (via description) batch_69b31c4665c081908d96878fc257fb76 completed March 12, 2026, 8:04 p.m.
Created at: March 8, 2026, 3:12 p.m.