Triple
T17889683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amalia Koutsouri-Vourekas |
E447281
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Amalia |
—
|
NE NERFINISHED |
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: Amalia | Statement: [Amalia Koutsouri-Vourekas, givenName, Amalia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amalia Context triple: [Amalia Koutsouri-Vourekas, givenName, Amalia]
-
A.
Amalia
Amalia is a character in Franz Kafka’s unfinished novel "The Castle," known for her defiant act that brings social ostracism upon her family.
-
B.
Amalia
Amalia is a novel by Finnish writer Sylvi Kekkonen, known for its introspective portrayal of women’s inner lives in mid-20th-century Finland.
-
C.
Amalia
chosen
Amalia is a feminine given name of Latin and Germanic origin, often associated with meanings related to work, industriousness, or striving.
-
D.
Amalia
Amalia is a pioneering 1914 Argentine silent film widely regarded as the first feature-length production in the history of Argentine cinema.
-
E.
Amalia
Amalia is a character in Mario Vargas Llosa’s novel "Conversación en La Catedral," representing one of the many figures entangled in the political and social decay of mid-20th-century Peru.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9f59bd48190a6fc925a855b8bac |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49d7828b481909b645fceb37a7ca3 |
completed | April 19, 2026, 9:16 a.m. |
Created at: April 10, 2026, 10:18 a.m.