Triple
T11493839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hotel Berlin |
E272482
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Andrea King |
E215313
|
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: Andrea King | Statement: [Hotel Berlin, castMember, Andrea King]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrea King Context triple: [Hotel Berlin, castMember, Andrea King]
-
A.
Andrea King
chosen
Andrea King was an American film and television actress best known for her roles in 1940s and 1950s Hollywood thrillers and dramas.
-
B.
Jessica King
Jessica King is a character in the supernatural thriller film "The Gift," involved in the mysterious events surrounding a small-town community.
-
C.
Andrea Waters King
Andrea Waters King is an American philanthropist and human rights advocate known for her work in social justice and for being married to civil rights leader Martin Luther King III.
-
D.
Nicole King
Nicole King is a film producer known for her work on the family comedy movie "Yes Day."
-
E.
Diana King
Diana King is a Jamaican singer-songwriter best known for her fusion of reggae, pop, and R&B, including hits like "Shy Guy" and acclaimed cover versions of classic songs.
- 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_69d6aae1b09881909ce2ded3fa0c14fa |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85ddffdf88190a00e94ad5b8b91a5 |
completed | April 10, 2026, 2:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6048a05c88190968f7827c5dd5342 |
completed | April 20, 2026, 10:48 a.m. |
Created at: April 8, 2026, 9:36 p.m.