Triple

T17614304
Position Surface form Disambiguated ID Type / Status
Subject Proença-a-Nova E429042 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object CB
CB is the vehicle registration code for the Castelo Branco district in central Portugal, which includes the municipality of Proença-a-Nova.
E1278400 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: CB | Statement: [Proença-a-Nova, hasVehicleRegistrationCode, CB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CB
Context triple: [Proença-a-Nova, hasVehicleRegistrationCode, CB]
  • A. CB
    CB is the post-nominal abbreviation indicating appointment as a Companion of the Order of the Bath, a British order of chivalry.
  • B. CB
    CB is a UK postcode area covering Cambridge and surrounding parts of Cambridgeshire and nearby regions.
  • C. CB
    CB is the vehicle registration code used on license plates for the German city of Cottbus.
  • D. CB
    CB is a common abbreviation for Code::Blocks, a free, open-source, cross-platform integrated development environment (IDE) primarily used for C, C++, and Fortran programming.
  • E. CB
    CB is the station code used to identify Taveiro railway station in Portugal’s rail network.
  • 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: CB
Triple: [Proença-a-Nova, hasVehicleRegistrationCode, CB]
Generated description
CB is the vehicle registration code for the Castelo Branco district in central Portugal, which includes the municipality of Proença-a-Nova.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: CB
Target entity description: CB is the vehicle registration code for the Castelo Branco district in central Portugal, which includes the municipality of Proença-a-Nova.
  • A. CB
    CB is the vehicle registration code assigned to cars registered in Bydgoszcz, a city in northern Poland.
  • B. CB
    CB is the vehicle registration code used for cars registered in the Czech city of České Budějovice.
  • C. CB
    CB is the station code used to identify Coimbra-B railway station in Portugal’s rail network.
  • D. CB
    CB is the station code used to identify Taveiro railway station in Portugal’s rail network.
  • E. CB
    CB is the vehicle registration code used on license plates for the German city of Cottbus.
  • 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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46d2fd96481908c9f3b566fca6907 completed April 19, 2026, 5:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01e8267d388190b97e038e142f338f completed May 11, 2026, 2:31 p.m.
NEDg Description generation batch_6a01f100fe5c81909bb43e89b60c27df completed May 11, 2026, 3:08 p.m.
NED2 Entity disambiguation (via description) batch_6a01f17a3efc81909404abb3a7ed6523 completed May 11, 2026, 3:10 p.m.
Created at: April 10, 2026, 5:51 a.m.