Triple

T16999015
Position Surface form Disambiguated ID Type / Status
Subject Liquid Paper E412389 entity
Predicate competesWith P1375 FINISHED
Object Tipp-Ex
Tipp-Ex is a well-known brand of correction fluid and related correction products commonly used to cover typing or writing errors on paper.
E1245178 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: Tipp-Ex | Statement: [Liquid Paper, competesWith, Tipp-Ex]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tipp-Ex
Context triple: [Liquid Paper, competesWith, Tipp-Ex]
  • A. Windex
    Windex is a popular household cleaning product best known for its blue glass cleaner used on windows and other hard surfaces.
  • B. Harpic
    Harpic is a widely used brand of toilet and bathroom cleaning products known for its powerful disinfecting and stain-removal formulations.
  • C. Drano
    Drano is a widely used household chemical product designed to clear clogged drains and pipes.
  • D. Mile-Ex
    Mile-Ex is a small, rapidly gentrifying Montreal neighborhood known for its mix of industrial spaces, creative studios, and trendy cafes.
  • E. Brillo
    Brillo is a lightweight, Android-based operating system developed by Google for powering and managing Internet of Things (IoT) devices.
  • 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: Tipp-Ex
Triple: [Liquid Paper, competesWith, Tipp-Ex]
Generated description
Tipp-Ex is a well-known brand of correction fluid and related correction products commonly used to cover typing or writing errors on paper.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tipp-Ex
Target entity description: Tipp-Ex is a well-known brand of correction fluid and related correction products commonly used to cover typing or writing errors on paper.
  • A. Windex
    Windex is a popular household cleaning product best known for its blue glass cleaner used on windows and other hard surfaces.
  • B. Harpic
    Harpic is a widely used brand of toilet and bathroom cleaning products known for its powerful disinfecting and stain-removal formulations.
  • C. Drano
    Drano is a widely used household chemical product designed to clear clogged drains and pipes.
  • D. Mile-Ex
    Mile-Ex is a small, rapidly gentrifying Montreal neighborhood known for its mix of industrial spaces, creative studios, and trendy cafes.
  • E. Brillo
    Brillo is a lightweight, Android-based operating system developed by Google for powering and managing Internet of Things (IoT) devices.
  • 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_69d886cb581c8190ab05f4b429c9cd85 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d37cd6248190a7202ae754882640 completed April 18, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc1ac518819093fac61b5598d730 completed May 10, 2026, 7:27 p.m.
NEDg Description generation batch_6a0114d68c8481909111bfab22882bb2 completed May 10, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a0118ba68408190b242154c40461f21 completed May 10, 2026, 11:46 p.m.
Created at: April 10, 2026, 5:32 a.m.