Triple
T8517994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malena |
E201623
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Milena |
E125468
|
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: Milena | Statement: [Malena, relatedName, Milena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Milena Context triple: [Malena, relatedName, Milena]
-
A.
Milena
chosen
Milena is the birth name of actress Mila Kunis, a Ukrainian-born American performer known for roles in "That '70s Show" and "Black Swan."
-
B.
Julita
Julita is a feminine given name, commonly used as a diminutive or variant of Julia in various languages and cultures.
-
C.
Muriel
Muriel is a feminine given name of French origin that has been borne by various notable figures, including politicians, writers, and artists.
-
D.
Tereza
Tereza is a feminine given name, commonly used in various European countries as a variant of Theresa.
-
E.
Veronika
Veronika is the troubled young protagonist of Paulo Coelho's novel "Veronika Decides to Die," whose suicide attempt leads her to a transformative stay in a mental institution.
- 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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe626787c819087e72dd76b2d9310 |
completed | March 31, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4e6c93d081909da2a748b0fa6fd3 |
completed | April 2, 2026, 11:09 a.m. |
Created at: March 30, 2026, 6:15 p.m.