Triple

T2889387
Position Surface form Disambiguated ID Type / Status
Subject LaTeX E59582 entity
Predicate hasEditor P1954 FINISHED
Object Kile
Kile is a KDE-based integrated LaTeX editor that provides tools for writing, compiling, and previewing LaTeX documents efficiently.
 E308581 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: Kile | Statement: [LaTeX, hasEditor, Kile]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kile
Context triple: [LaTeX, hasEditor, Kile]
  • A. Kivili
    Kivili is a regional dialect of the Kikongo language spoken by communities in parts of Central Africa.
  • B. Kaa
    Kaa is a giant, hypnotic python who serves as a dangerous and manipulative predator in Disney’s live-action adaptation of The Jungle Book.
  • C. Käina
    Käina is a small settlement on the Estonian island of Hiiumaa, known for its coastal landscapes and traditional rural character.
  • D. Kinel
    Kinel is a small industrial city in southwestern Russia that serves as a local transport and economic hub within Samara Oblast.
  • E. Kasoa
    Kasoa is a rapidly growing urban town in southern Ghana that serves as a major residential and commercial hub on the outskirts of Accra.
  • 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: Kile
Triple: [LaTeX, hasEditor, Kile]
Generated description
Kile is a KDE-based integrated LaTeX editor that provides tools for writing, compiling, and previewing LaTeX documents efficiently.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kile
Target entity description: Kile is a KDE-based integrated LaTeX editor that provides tools for writing, compiling, and previewing LaTeX documents efficiently.
  • A. Kivili
    Kivili is a regional dialect of the Kikongo language spoken by communities in parts of Central Africa.
  • B. Kaa
    Kaa is a giant, hypnotic python who serves as a dangerous and manipulative predator in Disney’s live-action adaptation of The Jungle Book.
  • C. Käina
    Käina is a small settlement on the Estonian island of Hiiumaa, known for its coastal landscapes and traditional rural character.
  • D. Kinel
    Kinel is a small industrial city in southwestern Russia that serves as a local transport and economic hub within Samara Oblast.
  • E. Kasoa
    Kasoa is a rapidly growing urban town in southern Ghana that serves as a major residential and commercial hub on the outskirts of Accra.
  • 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_69ab4ac739188190a112f42a5a69c951 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abe04a68ac8190aaeafe52138beb74 completed March 7, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69b03179d7448190bcdbea164856aaa2 completed March 10, 2026, 2:58 p.m.
NEDg Description generation batch_69b03f0c5bac81909aa21d5963a86c92 completed March 10, 2026, 3:55 p.m.
NED2 Entity disambiguation (via description) batch_69b044c1ea3c8190a9ae7c1431d3a3f2 completed March 10, 2026, 4:20 p.m.
Created at: March 6, 2026, 10:04 p.m.