Triple

T8608689
Position Surface form Disambiguated ID Type / Status
Subject GTK E203866 entity
Predicate component P35 FINISHED
Object Pango
Pango is a text layout and rendering library widely used in the GNOME/GTK ecosystem to provide internationalized, high-quality font and text handling.
E745749 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: Pango | Statement: [GTK, component, Pango]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pango
Context triple: [GTK, component, Pango]
  • A. Pango
    Pango is a coastal village on the island of Efate in Vanuatu, known for its traditional communities and proximity to the capital, Port Vila.
  • B. Uniscribe
    Uniscribe is a Windows text layout and shaping engine that provides complex script support, including advanced rendering and typographic features for scripts such as Arabic.
  • C. Pluma text editor
    Pluma text editor is a lightweight, user-friendly text editor commonly used in Linux environments as part of the MATE desktop ecosystem.
  • D. Font’s Point
    Font’s Point is a scenic overlook in California’s Anza-Borrego Desert famed for its sweeping sunrise views over the eroded badlands.
  • E. GTK
    GTK is a widely used open-source toolkit for creating graphical user interfaces, best known for powering applications in the GNOME desktop environment.
  • 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: Pango
Triple: [GTK, component, Pango]
Generated description
Pango is a text layout and rendering library widely used in the GNOME/GTK ecosystem to provide internationalized, high-quality font and text handling.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Pango
Target entity description: Pango is a text layout and rendering library widely used in the GNOME/GTK ecosystem to provide internationalized, high-quality font and text handling.
  • A. Pango
    Pango is a coastal village on the island of Efate in Vanuatu, known for its traditional communities and proximity to the capital, Port Vila.
  • B. Uniscribe
    Uniscribe is a Windows text layout and shaping engine that provides complex script support, including advanced rendering and typographic features for scripts such as Arabic.
  • C. Pluma text editor
    Pluma text editor is a lightweight, user-friendly text editor commonly used in Linux environments as part of the MATE desktop ecosystem.
  • D. Font’s Point
    Font’s Point is a scenic overlook in California’s Anza-Borrego Desert famed for its sweeping sunrise views over the eroded badlands.
  • E. GTK
    GTK is a widely used open-source toolkit for creating graphical user interfaces, best known for powering applications in the GNOME desktop environment.
  • 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_69ca832c23e4819095a9f3eea4a21828 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46ed77588190a872d22d9d1f7429 completed March 31, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea90dd93081908140ac0ce23be820 completed April 2, 2026, 5:36 p.m.
NEDg Description generation batch_69ceaa2c34308190a3bc7717012fea9d completed April 2, 2026, 5:41 p.m.
NED2 Entity disambiguation (via description) batch_69ceaae76d188190932826c9fd9f7f5f completed April 2, 2026, 5:44 p.m.
Created at: March 30, 2026, 6:25 p.m.