Triple

T12051876
Position Surface form Disambiguated ID Type / Status
Subject Northern Region, Uganda E286934 entity
Predicate hasCity P316 FINISHED
Object Lira E329618 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: Lira | Statement: [Northern Region, Uganda, hasCity, Lira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lira
Context triple: [Northern Region, Uganda, hasCity, Lira]
  • A. Lira chosen
    Lira is a major town in northern Uganda that serves as an important commercial and administrative center for the surrounding region.
  • B. Meram
    Meram is a central district and municipality of Konya in Turkey, known for its historic neighborhoods, gardens, and cultural heritage.
  • C. Darıca
    Darıca is a coastal town and district in northwestern Turkey, situated on the Sea of Marmara and known for its zoo, recreation areas, and proximity to Istanbul.
  • D. Ergene
    Ergene is a district and municipality in Turkey’s Tekirdağ Province, located in the European (Thrace) part of the country and known for its industrial activity.
  • E. Tolga
    Tolga is a town in northeastern Algeria known for its date palm oases and location within Biskra Province on the edge of the Sahara Desert.
  • 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90423b22081908fba82fbc6b40eb5 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49ddde6548190adae2a889ec5c72b completed May 1, 2026, 12:34 p.m.
Created at: April 8, 2026, 9:47 p.m.