Triple

T20835412
Position Surface form Disambiguated ID Type / Status
Subject Trnovo E512946 entity
Predicate hasMountain P10602 FINISHED
Object Igman NE NERFINISHED

How this triple was built (2 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: Igman | Statement: [Trnovo, hasMountain, Igman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Igman
Context triple: [Trnovo, hasMountain, Igman]
  • A. Igman chosen
    Igman is a mountain in central Bosnia and Herzegovina known for its forests, ski facilities, and role as a key venue during the 1984 Winter Olympics near Sarajevo.
  • B. Kopaska
    Kopaska is the Indonesian Navy’s elite frogman and special operations unit, specializing in underwater demolition, maritime sabotage, and counter-terrorism missions.
  • C. Veliki Borak
    Veliki Borak is a village located within the Barajevo municipality in the wider Belgrade region of Serbia.
  • D. Ijemo
    Ijemo is a neighborhood and traditional community within the city of Abeokuta in Ogun State, southwestern Nigeria.
  • E. Oreshak
    Oreshak is a village in central Bulgaria known for its proximity to the historic Troyan Monastery and its traditional crafts and cultural heritage.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4cf62a88190bbf92351e9e57259 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c32622c481908b8d2159bd5bb0ad completed April 21, 2026, 12:21 a.m.
Created at: April 16, 2026, 12:42 p.m.