Triple
T16035291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Icíar Bollaín |
E388954
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object | Yuli |
E904109
|
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: Yuli | Statement: [Icíar Bollaín, directed, Yuli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yuli Context triple: [Icíar Bollaín, directed, Yuli]
-
A.
Yuli
chosen
Yuli is a film for which screenwriter Paul Laverty wrote the screenplay, likely reflecting his characteristic focus on socially conscious, character-driven storytelling.
-
B.
Oksana
Oksana is a feminine given name of Ukrainian origin, most famously borne by Olympic champion figure skater Oksana Baiul.
-
C.
Yelena
Yelena is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and equivalent to Helen or Helena in English.
-
D.
Yulania
Yulania is a genus of flowering plants in the magnolia family, known for its ornamental, often early-blooming trees and shrubs.
-
E.
Yulia
Yulia is a feminine given name, commonly used in Slavic countries as a form of the name Julia.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1833b84608190887dafda5d081dc0 |
completed | April 17, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe474f89c819086db832b793c15ed |
completed | May 10, 2026, 1:50 a.m. |
Created at: April 10, 2026, 4:56 a.m.