Triple

T10415980
Position Surface form Disambiguated ID Type / Status
Subject PPG Industries E245516 entity
Predicate hasBrand P1500 FINISHED
Object Glidden
Glidden is a well-known American paint brand offering a wide range of interior and exterior paints for consumers and professionals.
 E839066 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: Glidden | Statement: [PPG Industries, hasBrand, Glidden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Glidden
Context triple: [PPG Industries, hasBrand, Glidden]
  • A. Benjamin Moore
    Benjamin Moore was an American Episcopal bishop and academic who served as the second bishop of New York and president of Columbia College in the early 19th century.
  • B. PPG
    PPG is the IATA airport code for Pago Pago International Airport, the main air gateway to American Samoa.
  • C. BASF Coatings
    BASF Coatings is a BASF subsidiary specializing in the development and production of automotive, industrial, and decorative coating solutions.
  • D. Mannington
    Mannington is a small settlement in Norfolk, England, situated near the historic Wolterton estate.
  • E. Dalmine
    Dalmine is an industrial town in northern Italy known for its steel production and manufacturing activities.
  • 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: Glidden
Triple: [PPG Industries, hasBrand, Glidden]
Generated description
Glidden is a well-known American paint brand offering a wide range of interior and exterior paints for consumers and professionals.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Glidden
Target entity description: Glidden is a well-known American paint brand offering a wide range of interior and exterior paints for consumers and professionals.
  • A. Benjamin Moore
    Benjamin Moore was an American Episcopal bishop and academic who served as the second bishop of New York and president of Columbia College in the early 19th century.
  • B. PPG
    PPG is the IATA airport code for Pago Pago International Airport, the main air gateway to American Samoa.
  • C. BASF Coatings chosen
    BASF Coatings is a BASF subsidiary specializing in the development and production of automotive, industrial, and decorative coating solutions.
  • D. Mannington
    Mannington is a small settlement in Norfolk, England, situated near the historic Wolterton estate.
  • E. Dalmine
    Dalmine is an industrial town in northern Italy known for its steel production and manufacturing activities.
  • F. None of above.

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_69d381be340c8190b05998703d42d224 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea108fec8190819423630888fa2b completed April 7, 2026, 11:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fc0dd480819082edcc49a245ad4f completed April 9, 2026, 7:20 p.m.
NEDg Description generation batch_69d822d6a0188190a7ee6de5aab50486 completed April 9, 2026, 10:06 p.m.
NED2 Entity disambiguation (via description) batch_69d859e40bf88190a6dc8deed3049d31 completed April 10, 2026, 2:01 a.m.
Created at: April 6, 2026, 12:10 p.m.