Triple

T4182242
Position Surface form Disambiguated ID Type / Status
Subject Lake Peipus E88220 entity
Predicate borderCity P15361 FINISHED
Object Tartu E43129 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: Tartu | Statement: [Lake Peipus, borderCity, Tartu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tartu
Context triple: [Lake Peipus, borderCity, Tartu]
  • A. Tartu chosen
    Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
  • B. Tallinn
    Tallinn is the capital and largest city of Estonia, a historic Baltic Sea port known for its well-preserved medieval Old Town and strategic maritime location.
  • C. Pärnu
    Pärnu is a coastal city in southwestern Estonia known as a popular summer resort and spa destination on the Baltic Sea.
  • D. Viljandi
    Viljandi is a historic town in southern Estonia known for its medieval castle ruins, rich cultural life, and annual folk music festival.
  • E. Reval
    Reval is the historical German name for Tallinn, the capital city and major port of present-day Estonia on the Baltic Sea.
  • 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_69aed9477e8c81908bcb862d2db55b1d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0305e2e88190a51f176f8534f1f9 completed March 9, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a849cdac8190b12ac2a0e42c3b53 completed March 14, 2026, 6:26 p.m.
Created at: March 9, 2026, 3:45 p.m.