Triple

T17273873
Position Surface form Disambiguated ID Type / Status
Subject Olga Masaryková E419334 entity
Predicate familyName P18 FINISHED
Object Masaryková E1257567 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: Masaryková | Statement: [Olga Masaryková, familyName, Masaryková]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Masaryková
Context triple: [Olga Masaryková, familyName, Masaryková]
  • A. Masaryková chosen
    Masaryková is a Czech surname most notably borne by members of the Masaryk family, including sociologist and politician Alice Masaryková.
  • B. Nemšová
    Nemšová is a small town in western Slovakia known for its location near the Czech border and the Váh River within the Trenčín administrative area.
  • C. Hradčanská
    Hradčanská is a Prague Metro station on Line A located near Prague Castle in the Hradčany district.
  • D. Němcová
    Němcová is a Czech surname most famously borne by Božena Němcová, a pioneering 19th-century Czech writer and key figure of the Czech National Revival.
  • E. Libuše
    Libuše is a Czech opera by Bedřich Smetana, centered on the legendary princess Libuše who prophesies the glory of Prague and the Czech nation.
  • 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_69d886da626481908a14ce7830329a35 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42f4c209c81909c713ed78f2cb19a completed April 19, 2026, 1:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01794d605481908b5e430c3142c203 completed May 11, 2026, 6:38 a.m.
Created at: April 10, 2026, 5:40 a.m.