Triple

T11457756
Position Surface form Disambiguated ID Type / Status
Subject Terézia Mora E271573 entity
Predicate givenName P17 FINISHED
Object Terézia E271573 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: Terézia | Statement: [Terézia Mora, givenName, Terézia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terézia
Context triple: [Terézia Mora, givenName, Terézia]
  • A. Terézia chosen
    Terézia is the given name of the Hungarian-born German writer and translator Terézia Mora, known for her award-winning novels and screenplays.
  • B. Josepha
    Josepha is the given name of Maria Josepha Amalia of Saxony, a 19th-century Saxon princess who became Queen consort of Spain as the third wife of King Ferdinand VII.
  • C. Agnes of Bohemia
    Agnes of Bohemia was a medieval Bohemian princess and member of the Přemyslid dynasty, known primarily as the daughter of King Wenceslaus II of Bohemia.
  • D. Mária
    Mária is the Hungarian and Slovak form of the given name Mary, commonly used in Central and Eastern Europe.
  • E. Hedvig
    Hedvig is a Scandinavian female given name, historically borne by several notable women in Swedish and broader Nordic royalty and nobility.
  • 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_69d6aadff8888190a13f253f0d460874 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d81c71b1208190be1d5623d18e0222 completed April 9, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ee866bb71c819091573965f7cf0dee completed April 26, 2026, 9:40 p.m.
Created at: April 8, 2026, 9:35 p.m.