Triple

T7608268
Position Surface form Disambiguated ID Type / Status
Subject Hungarian Sea E180163 entity
Predicate languageEquivalent P28329 FINISHED
Object Magyar tenger E180163 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: Magyar tenger | Statement: [Hungarian Sea, languageEquivalent, Magyar tenger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magyar tenger
Context triple: [Hungarian Sea, languageEquivalent, Magyar tenger]
  • A. Hungarian Sea chosen
    The "Hungarian Sea" is a popular nickname for Lake Balaton, Central Europe’s largest lake and a major holiday and recreation destination in Hungary.
  • B. Meer
    Meer is a surname of South Asian origin borne by numerous individuals, including notable figures in politics, academia, and the arts.
  • C. Veerse Meer
    Veerse Meer is a coastal lagoon and recreational lake in the Dutch province of Zeeland, popular for water sports and nature conservation.
  • D. Trälhavet
    Trälhavet is a bay in the Stockholm archipelago of Sweden, known for its boating routes and connection to surrounding inlets and waterways.
  • E. Meeri
    Meeri is the inner fortification complex located within Pakistan’s historic Ranikot Fort, often noted for its distinct defensive walls and gateways.
  • 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_69c69f3567008190ab01d2ca7b53584a completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6fa1de8a4819091f9e9347835ce16 completed March 27, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8685c050c8190b05fa19c9ae2c827 completed March 28, 2026, 11:46 p.m.
Created at: March 27, 2026, 3:54 p.m.