Triple

T19228435
Position Surface form Disambiguated ID Type / Status
Subject Armistice of Mudanya E480803 entity
Predicate location P40 FINISHED
Object Mudanya 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: Mudanya | Statement: [Armistice of Mudanya, location, Mudanya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mudanya
Context triple: [Armistice of Mudanya, location, Mudanya]
  • A. Mudanya chosen
    Mudanya is a coastal town and district in Bursa Province, northwestern Turkey, situated along the Sea of Marmara and known for its port, historic architecture, and role in the Turkish War of Independence.
  • B. Nimule
    Nimule is a South Sudanese border town near Uganda that serves as a key trade and transport hub in the region.
  • C. Kiryandongo
    Kiryandongo is a town in western Uganda that serves as the administrative and commercial center of Kiryandongo District.
  • D. Tontemboan
    Tontemboan is an Austronesian language spoken by the Tontemboan people in North Sulawesi, Indonesia.
  • E. Kaltungo
    Kaltungo is a town and administrative center in northeastern Nigeria known for its role as one of the local government areas within Gombe State.
  • 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_69d8e8ccb8f48190ad420098e74fb1db completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fa9b167881908fc46d46c2d53423 completed April 20, 2026, 10:06 a.m.
Created at: April 10, 2026, 1:25 p.m.