Triple

T6998737
Position Surface form Disambiguated ID Type / Status
Subject California Department of Rehabilitation E162281 entity
Predicate hasAbbreviation P43 FINISHED
Object DOR
DOR is the California state agency that provides vocational rehabilitation and related services to help individuals with disabilities prepare for, obtain, and retain employment.
 E634505 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: [California Department of Rehabilitation, hasAbbreviation, DOR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DOR
Context triple: [California Department of Rehabilitation, hasAbbreviation, DOR]
  • A. DOR
    DOR is the standard abbreviation used for the Mexican football club Dorados de Sinaloa.
  • B. DOR
    DOR is the vehicle registration code used on license plates for the English county of Dorset.
  • C. DUR
    DUR is the IATA airport code for King Shaka International Airport serving Durban, South Africa.
  • D. DAR
    DAR is the Philippine government agency responsible for implementing agrarian reform and redistributing agricultural land to farmers.
  • E. 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.
  • 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: [California Department of Rehabilitation, hasAbbreviation, DOR]
Generated description
DOR is the California state agency that provides vocational rehabilitation and related services to help individuals with disabilities prepare for, obtain, and retain employment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DOR
Target entity description: DOR is the California state agency that provides vocational rehabilitation and related services to help individuals with disabilities prepare for, obtain, and retain employment.
  • A. DOR
    DOR is the standard abbreviation used for the Mexican football club Dorados de Sinaloa.
  • B. DOR
    DOR is the vehicle registration code used on license plates for the English county of Dorset.
  • C. DUR
    DUR is the IATA airport code for King Shaka International Airport serving Durban, South Africa.
  • D. DAR
    DAR is the Philippine government agency responsible for implementing agrarian reform and redistributing agricultural land to farmers.
  • E. 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.
  • 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_69c68857ffc08190857dc62cd5253777 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dbf083b481909dd30e28e908dfdf completed March 27, 2026, 7:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a2c510c8190b7c86f8b399388ae completed March 28, 2026, 5:42 a.m.
NEDg Description generation batch_69c76b1d881481908ef5a6614246ca1e completed March 28, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69c76be95ecc8190a57ff197f236d434 completed March 28, 2026, 5:49 a.m.
Created at: March 27, 2026, 2:33 p.m.