Triple
T22404292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teresa |
E553842
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Tereza |
E728423
|
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: Tereza | Statement: [Teresa, hasVariant, Tereza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tereza Context triple: [Teresa, hasVariant, Tereza]
-
A.
Tereza
chosen
Tereza is a feminine given name, commonly used in various European countries as a variant of Theresa.
-
B.
Tereza Vávrová
Tereza Vávrová is a notable bearer of the Czech surname Vávrová, recognized enough to be specifically cited in reference to the name.
-
C.
Antónia
Antónia is a feminine given name commonly used in various European languages, often as a variant of Antonia.
-
D.
Veronika Bellmann
Veronika Bellmann is a German politician known for her long-standing membership in the Bundestag representing the Christian Democratic Union (CDU).
-
E.
Milada
Milada is a feminine given name of Slavic origin, particularly common in Czech and Slovak cultures.
- 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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158b6762c8190991fc14c5ca8e609 |
completed | April 29, 2026, 1:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ae9cfabe081908d6a001bcfe5372c |
completed | May 18, 2026, 10:28 a.m. |
Created at: April 16, 2026, 8:46 p.m.