Triple

T6921900
Position Surface form Disambiguated ID Type / Status
Subject Mir E160204 entity
Predicate hasAlternativeTransliteration P5923 FINISHED
Object Meer E449050 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: Meer | Statement: [Mir, hasAlternativeTransliteration, Meer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meer
Context triple: [Mir, hasAlternativeTransliteration, Meer]
  • A. Meer chosen
    Meer is a surname of South Asian origin borne by numerous individuals, including notable figures in politics, academia, and the arts.
  • B. Veerse Meer
    Veerse Meer is a coastal lagoon and recreational lake in the Dutch province of Zeeland, popular for water sports and nature conservation.
  • C. Hollands Diep
    Hollands Diep is a broad estuarine river and former sea arm in the southwestern Netherlands that forms part of the Rhine–Meuse–Scheldt delta system.
  • D. Meeri
    Meeri is the inner fortification complex located within Pakistan’s historic Ranikot Fort, often noted for its distinct defensive walls and gateways.
  • E. Zuiderzee
    The Zuiderzee was a former shallow inlet of the North Sea in the northwest of the Netherlands that played a major role in Dutch maritime trade and was later transformed into the freshwater IJsselmeer by large-scale land reclamation works.
  • 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_69c6884d350081908d8a970e4d40ad78 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d9fb8ac48190b50bbc47fad8288f completed March 27, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c75137dd848190b35ff72725f886ba completed March 28, 2026, 3:55 a.m.
Created at: March 27, 2026, 2:26 p.m.