Triple
T21569924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elisa Claro |
E532257
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Elisa |
—
|
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: Elisa | Statement: [Elisa Claro, givenName, Elisa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elisa Context triple: [Elisa Claro, givenName, Elisa]
-
A.
Elisa
Elisa is the central protagonist of the animated series "High Seas," around whom the show's main adventures and storylines revolve.
-
B.
Elisa
Elisa is a French drama film directed by Jean Becker, known for its emotional story and strong performances.
-
C.
Elisa
chosen
Elisa is a feminine given name of Hebrew origin, often considered a short form of Elisabeth and used in various languages including Italian, Spanish, and French.
-
D.
Elisa
Elisa is a major Finnish telecommunications and digital services company providing mobile, broadband, and TV solutions.
-
E.
Elisa Bell
Elisa Bell is a screenwriter best known for her work on the comedy film "Vegas Vacation."
- 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_69e0c460db088190828c64206a450273 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eee9cb9718819094fc95b25df68bd1 |
completed | April 27, 2026, 4:44 a.m. |
Created at: April 16, 2026, 6:30 p.m.