Triple

T15394417
Position Surface form Disambiguated ID Type / Status
Subject Anna Szafranek "Hanka" E368133 entity
Predicate usedAlias P3799 FINISHED
Object Hanka E991436 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: Hanka | Statement: [Anna Szafranek "Hanka", usedAlias, Hanka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanka
Context triple: [Anna Szafranek "Hanka", usedAlias, Hanka]
  • A. Haná
    Haná is a historical ethnographic region in central Moravia in the Czech Republic, known for its fertile agricultural land, distinctive folk traditions, and Hanakian dialect.
  • B. Katinka
    Katinka is a 1915 operetta composed by Rudolf Friml, known for its light romantic plot and melodic score typical of early 20th-century musical theatre.
  • C. Henryka chosen
    Henryka is a Polish feminine given name derived from the male name Henryk.
  • D. Lány
    Lány is a village and chateau area in the Czech Republic known as the site of the presidential summer residence and the place where the first Czechoslovak president Tomáš Garrigue Masaryk died.
  • E. Hanneli
    Hanneli is the nickname of Hannah Elisabeth Goslar, a Jewish Holocaust survivor best known as a close childhood friend of Anne Frank.
  • 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_69d85a1551a08190ba2caea7cd51c639 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e8ac79081908ac79c0b3e7587ff completed April 16, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff13523f548190beafd130f8741465 completed May 9, 2026, 10:58 a.m.
Created at: April 10, 2026, 3:19 a.m.