Triple
T5834777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rebekah Elmaloglou |
E129439
|
entity |
| Predicate | castMemberOf |
P7010
|
FINISHED |
| Object | G.P. |
E549574
|
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: G.P. | Statement: [Rebekah Elmaloglou, castMemberOf, G.P.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: G.P. Context triple: [Rebekah Elmaloglou, castMemberOf, G.P.]
-
A.
G.P.
chosen
G.P. is an Australian television drama series best known for its portrayal of the professional and personal lives of doctors in a suburban general medical practice.
-
B.
GP
GP is the vehicle registration code used on license plates for the German town and district of Göppingen in the state of Baden-Württemberg.
-
C.
GP
GP is the two-letter ISO 3166-1 alpha-2 country code assigned to Guadeloupe.
-
D.
GPP
GPP is a fictional technology from Douglas Adams' "The Hitchhiker's Guide to the Galaxy" universe that endows machines with human-like personalities and emotions.
-
E.
The G
The G is the popular nickname for the Melbourne Cricket Ground, one of the world’s largest and most iconic sports stadiums located in Melbourne, Australia.
- 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_69c0084af79c81908af128ccc29983d0 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c034a1e6a88190b1aac05511793315 |
completed | March 22, 2026, 6:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b0ef1c988190b452158b560cf39f |
completed | March 23, 2026, 3:18 a.m. |
Created at: March 22, 2026, 3:54 p.m.