Triple
T16229522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flashdance |
E393941
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Lilia Skala |
E228097
|
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: Lilia Skala | Statement: [Flashdance, castMember, Lilia Skala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lilia Skala Context triple: [Flashdance, castMember, Lilia Skala]
-
A.
Lilia Skala
chosen
Lilia Skala was an Austrian-American actress and architect best known for her Academy Award–nominated role in the film "Lilies of the Field."
-
B.
Albina Vas
Albina Vas is known as the wife of Hungarian Nobel Prize–winning author Imre Kertész.
-
C.
Katerina Brac
Katerina Brac is a poetry collection by British poet Christopher Reid, presented as the translated works of an invented Eastern European poet of the same name.
-
D.
Tatiana Lappa
Tatiana Lappa was the first wife of Russian writer Mikhail Bulgakov, known primarily through biographical accounts of his early life and career.
-
E.
Ekaterina Gradova
Ekaterina Gradova was a Soviet and Russian actress best known for her roles in popular 1970s film and television productions.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d2889688190ac04e4e9479cabf4 |
completed | April 17, 2026, 2:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000ed71f488190bcdc2dcc74e5c5d3 |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 5:03 a.m.