Triple

T5335564
Position Surface form Disambiguated ID Type / Status
Subject Sarajevo Canton E123817 entity
Predicate contains P35 FINISHED
Object Trnovo
Trnovo is a small mountainous municipality in Bosnia and Herzegovina known for its natural landscapes and proximity to Sarajevo.
 E512946 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: Trnovo | Statement: [Sarajevo Canton, contains, Trnovo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Trnovo
Context triple: [Sarajevo Canton, contains, Trnovo]
  • A. Troinex
    Troinex is a small municipality in the canton of Geneva in southwestern Switzerland, situated near the French border.
  • B. Bornova
    Bornova is a populous district of İzmir, Turkey, known for its large university campus, residential neighborhoods, and role as a key suburban hub of the city.
  • C. Zenta
    Zenta is a historic town in northern Serbia, best known as the site of a decisive 1697 battle between the Habsburg Monarchy and the Ottoman Empire.
  • D. Transtu
    Transtu is the public transport authority in Tunis responsible for operating the city’s metro and other urban transit services.
  • E. Novellae
    Novellae are the later imperial constitutions of Emperor Justinian I that supplemented and updated his earlier codification of Roman law within the Corpus Juris Civilis.
  • 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: Trnovo
Triple: [Sarajevo Canton, contains, Trnovo]
Generated description
Trnovo is a small mountainous municipality in Bosnia and Herzegovina known for its natural landscapes and proximity to Sarajevo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Trnovo
Target entity description: Trnovo is a small mountainous municipality in Bosnia and Herzegovina known for its natural landscapes and proximity to Sarajevo.
  • A. Troinex
    Troinex is a small municipality in the canton of Geneva in southwestern Switzerland, situated near the French border.
  • B. Bornova
    Bornova is a populous district of İzmir, Turkey, known for its large university campus, residential neighborhoods, and role as a key suburban hub of the city.
  • C. Zenta
    Zenta is a historic town in northern Serbia, best known as the site of a decisive 1697 battle between the Habsburg Monarchy and the Ottoman Empire.
  • D. Transtu
    Transtu is the public transport authority in Tunis responsible for operating the city’s metro and other urban transit services.
  • E. Novellae
    Novellae are the later imperial constitutions of Emperor Justinian I that supplemented and updated his earlier codification of Roman law within the Corpus Juris Civilis.
  • 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_69bd464b07f8819095aa76577c9829e4 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85af799081909ee60bfbb65149ee completed March 20, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf18be4bb88190a2b83e51716e677e completed March 21, 2026, 10:16 p.m.
NEDg Description generation batch_69bf194c53a48190b0895bbe9aa2f6f1 completed March 21, 2026, 10:18 p.m.
NED2 Entity disambiguation (via description) batch_69bf1a198418819089b25102733f9191 completed March 21, 2026, 10:22 p.m.
Created at: March 20, 2026, 2 p.m.