Triple

T7733798
Position Surface form Disambiguated ID Type / Status
Subject Tolima volcano E175329 entity
Predicate primaryAccessTown P22318 FINISHED
Object Ibagué E174123 NE FINISHED

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: Ibagué | Statement: [Tolima volcano, primaryAccessTown, Ibagué]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ibagué
Context triple: [Tolima volcano, primaryAccessTown, Ibagué]
  • A. Tunja
    Tunja is a historic city in central Colombia known for its well-preserved colonial architecture and cultural heritage.
  • B. Suesca
    Suesca is a Colombian town in the department of Cundinamarca, renowned for its dramatic rock cliffs that make it a popular destination for rock climbing and outdoor recreation.
  • C. Bucaramanga
    Bucaramanga is a major city in northeastern Colombia known for its mountainous setting, pleasant climate, and role as an important commercial and industrial center.
  • D. Manizales
    Manizales is a mountainous Colombian city known for its coffee production, cool climate, and location in the central Andes.
  • E. Ibagué urban area chosen
    The Ibagué urban area is the principal metropolitan and economic center surrounding the city of Ibagué in central Colombia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c6995e912c81909a49a2657103f786 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c70339c4b481909a56ae13f501e794 completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c91b1bd9148190931ce1a2a42f729b completed March 29, 2026, 12:29 p.m.
Created at: March 27, 2026, 4:06 p.m.