Triple
T11082639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marisa Tomei |
E262040
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Marisa |
E195715
|
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: Marisa | Statement: [Marisa Tomei, givenName, Marisa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marisa Context triple: [Marisa Tomei, givenName, Marisa]
-
A.
Marisa
chosen
Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
-
B.
Maira
Maira is a given name used in various cultures, often as a variant of names like Maera, Maria, or Mary.
-
C.
Marzelline
Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
-
D.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
-
E.
Marisus
Marisus is the historical Latin name for the Mureș River, a major waterway flowing through present-day Romania and Hungary.
- 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799bf89f48190889f08d2f5dd220a |
completed | April 9, 2026, 12:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3e789d7248190a40de0bdda539f45 |
completed | April 18, 2026, 8:20 p.m. |
Created at: April 8, 2026, 9:27 p.m.