Triple

T2823635
Position Surface form Disambiguated ID Type / Status
Subject Torfaen E54866 entity
Predicate ISO3166-2Code P208 FINISHED
Object GB-TOF
GB-TOF is the ISO 3166-2 subdivision code assigned to the county borough of Torfaen in Wales, United Kingdom.
 E301112 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: GB-TOF | Statement: [Torfaen, ISO3166-2Code, GB-TOF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GB-TOF
Context triple: [Torfaen, ISO3166-2Code, GB-TOF]
  • A. SCIEX
    SCIEX is a leading analytical instrumentation company best known for its mass spectrometry and capillary electrophoresis technologies used in life sciences and analytical laboratories.
  • B. TMB 4000 series
    The TMB 4000 series is a class of electric multiple unit trains used on the Barcelona Metro system for passenger service.
  • C. Cobas
    Cobas is Roche's line of automated clinical laboratory analyzers and diagnostic systems widely used for blood testing and other in vitro diagnostics.
  • D. TMB 5000 series
    The TMB 5000 series is a class of modern electric multiple unit trains used on the Barcelona Metro network.
  • E. TMB 3000 series
    The TMB 3000 series is a class of electric multiple unit trains used on the Barcelona Metro system for passenger service.
  • 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: GB-TOF
Triple: [Torfaen, ISO3166-2Code, GB-TOF]
Generated description
GB-TOF is the ISO 3166-2 subdivision code assigned to the county borough of Torfaen in Wales, United Kingdom.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GB-TOF
Target entity description: GB-TOF is the ISO 3166-2 subdivision code assigned to the county borough of Torfaen in Wales, United Kingdom.
  • A. SCIEX
    SCIEX is a leading analytical instrumentation company best known for its mass spectrometry and capillary electrophoresis technologies used in life sciences and analytical laboratories.
  • B. TMB 4000 series
    The TMB 4000 series is a class of electric multiple unit trains used on the Barcelona Metro system for passenger service.
  • C. Cobas
    Cobas is Roche's line of automated clinical laboratory analyzers and diagnostic systems widely used for blood testing and other in vitro diagnostics.
  • D. TMB 5000 series
    The TMB 5000 series is a class of modern electric multiple unit trains used on the Barcelona Metro network.
  • E. TMB 3000 series
    The TMB 3000 series is a class of electric multiple unit trains used on the Barcelona Metro system for passenger service.
  • 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_69ab49e100c0819082a40cb797383243 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde71fdc08190b18660261fe24adf completed March 7, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69afcead12588190bfbb2c9e93b05e0d completed March 10, 2026, 7:56 a.m.
NEDg Description generation batch_69afcf5ec0a481909061d50877429f3b completed March 10, 2026, 7:59 a.m.
NED2 Entity disambiguation (via description) batch_69afcff778748190978e7d306e0d1ce1 completed March 10, 2026, 8:01 a.m.
Created at: March 6, 2026, 9:59 p.m.