Triple
T10402995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maya Plisetskaya |
E245192
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Carmen Suite |
E36362
|
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: Carmen Suite | Statement: [Maya Plisetskaya, notableWork, Carmen Suite]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carmen Suite Context triple: [Maya Plisetskaya, notableWork, Carmen Suite]
-
A.
Carmen
Carmen is a pivotal character in the 1986 film "The Color of Money," serving as the savvy and manipulative girlfriend-manager of young pool hustler Vincent Lauria.
-
B.
Carmen
Carmen is a key character in the dark fantasy film "Pan’s Labyrinth," serving as the pregnant mother whose fragile health and marriage to a brutal captain frame the story’s wartime and familial tensions.
-
C.
Carmen
Carmen is a landlocked municipality in the central part of Bohol Island in the Philippines, known for its proximity to the famous Chocolate Hills.
-
D.
Carmen
chosen
Carmen is a famous opera by Georges Bizet, renowned for its passionate music and tragic story centered on the free-spirited gypsy Carmen.
-
E.
Carmen
Carmen is a central district of San José, Costa Rica, known for its urban character and role in the capital’s administrative and commercial life.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9e535d48190b8fc377df543e058 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fbdb86788190bb1a8802f713fea2 |
completed | April 9, 2026, 7:19 p.m. |
Created at: April 6, 2026, 12:08 p.m.