Triple

T10608458
Position Surface form Disambiguated ID Type / Status
Subject Penske Media Corporation E275938 entity
Predicate hasBrand P1500 FINISHED
Object BGR
BGR is a technology and entertainment news website known for its coverage of consumer electronics, mobile devices, and digital culture.
E874227 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: BGR | Statement: [Penske Media Corporation, hasBrand, BGR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BGR
Context triple: [Penske Media Corporation, hasBrand, BGR]
  • A. BGR
    BGR is the three-letter ISO 3166-1 alpha-3 country code assigned to Bulgaria.
  • B. BGR
    BGR is the three-letter IATA airport code for Bangor International Airport in Bangor, Maine, United States.
  • C. BRG
    BRG is the stock ticker symbol for Borregaard, a Norwegian company specializing in advanced and sustainable biochemicals derived from wood.
  • D. RYG
    RYG is the IATA airport code for Moss Airport, Rygge, a former civil and military airport in southeastern Norway.
  • E. KBGR
    KBGR is the ICAO airport code for Bangor International Airport, a public airport serving Bangor, Maine, in the United States.
  • 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: BGR
Triple: [Penske Media Corporation, hasBrand, BGR]
Generated description
BGR is a technology and entertainment news website known for its coverage of consumer electronics, mobile devices, and digital culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: BGR
Target entity description: BGR is a technology and entertainment news website known for its coverage of consumer electronics, mobile devices, and digital culture.
  • A. BGR
    BGR is the three-letter ISO 3166-1 alpha-3 country code assigned to Bulgaria.
  • B. BGR
    BGR is the three-letter IATA airport code for Bangor International Airport in Bangor, Maine, United States.
  • C. BRG
    BRG is the stock ticker symbol for Borregaard, a Norwegian company specializing in advanced and sustainable biochemicals derived from wood.
  • D. RYG
    RYG is the IATA airport code for Moss Airport, Rygge, a former civil and military airport in southeastern Norway.
  • E. KBGR
    KBGR is the ICAO airport code for Bangor International Airport, a public airport serving Bangor, Maine, in the United States.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6df4c38c881908f69bb757b8e03f5 completed April 8, 2026, 11:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69d95ebe539881908aeff1cd65cf925f completed April 10, 2026, 8:34 p.m.
NEDg Description generation batch_69d95f81955c8190b629d57a034a4b76 completed April 10, 2026, 8:37 p.m.
NED2 Entity disambiguation (via description) batch_69d961047a78819088094e02c0b99f60 completed April 10, 2026, 8:43 p.m.
Created at: April 8, 2026, 7:32 p.m.