Triple

T3108528
Position Surface form Disambiguated ID Type / Status
Subject Mother Teresa E64893 entity
Predicate birthPlace P1 FINISHED
Object Skopje E33001 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: Skopje | Statement: [Mother Teresa, birthPlace, Skopje]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skopje
Context triple: [Mother Teresa, birthPlace, Skopje]
  • A. Skopje chosen
    Skopje is the capital and largest city of North Macedonia, known for its historic Ottoman and Byzantine heritage alongside extensive modern redevelopment.
  • B. Mitrovica
    Mitrovica is a divided city in northern Kosovo known for its ethnic tensions and strategic importance as a regional industrial and mining center.
  • C. Monastir
    Monastir, known today as Bitola in North Macedonia, is a historic Balkan city that played a significant strategic role during World War I.
  • D. Pristina
    Pristina is the capital and largest city of Kosovo, serving as its political, economic, and cultural center in the central Balkans.
  • E. Prizren
    Prizren is a historic and culturally rich city in southern Kosovo, known for its well-preserved Ottoman-era architecture and diverse religious heritage.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada29eacc88190a19c5ca8e53e3dca completed March 8, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b203902a6881909b20589fad629640 completed March 12, 2026, 12:06 a.m.
Created at: March 8, 2026, 3:04 p.m.