Triple

T710920
Position Surface form Disambiguated ID Type / Status
Subject Sinews of Peace E14203 entity
Predicate mentions P831 FINISHED
Object Bucharest E31636 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: Bucharest | Statement: [Sinews of Peace, mentions, Bucharest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bucharest
Context triple: [Sinews of Peace, mentions, Bucharest]
  • A. Bucharest chosen
    Bucharest is the capital and largest city of Romania, known for its mix of historic architecture, wide boulevards, and its role as the country’s political, cultural, and economic center.
  • B. Galați
    Galați is a major Romanian port city in eastern Romania, situated near the border with Moldova and known for its shipbuilding and steel industries.
  • C. Constanța
    Constanța is a major Romanian coastal city and one of the largest and most important ports on the Black Sea.
  • D. Sofia
    Sofia is the capital and largest city of Bulgaria, known as a major cultural, economic, and historical center in the Balkans.
  • E. Râmnicu Vâlcea
    Râmnicu Vâlcea is a city in south-central Romania, located on the Olt River and serving as the capital of Vâlcea County.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a55c99fc8190941c5fd18551792a completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a6733031bc8190bbb0cd733ae023e9 completed March 3, 2026, 5:35 a.m.
Created at: March 1, 2026, 7:36 p.m.