Triple
T22234999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kane Baker |
E549568
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Rebekah Elmaloglou |
—
|
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: Rebekah Elmaloglou | Statement: [Kane Baker, spouse, Rebekah Elmaloglou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rebekah Elmaloglou Context triple: [Kane Baker, spouse, Rebekah Elmaloglou]
-
A.
Rebekah Elmaloglou
chosen
Rebekah Elmaloglou is an Australian actress best known for her long-running role as Terese Willis on the soap opera "Neighbours."
-
B.
Alix Pahlavouni
Alix Pahlavouni was a noblewoman of the Armenian Kingdom of Cilicia and a member of the influential Pahlavuni family, known primarily as the queen consort and mother of King Hethum I.
-
C.
Lila Yacoub
Lila Yacoub is a film producer known for her work on independent features such as Noah Baumbach’s comedy-drama "Mistress America."
-
D.
Alexis Demetriades
Alexis Demetriades is an individual known for being professionally trained by Michael Page.
-
E.
Isabel Bayrakdarian
Isabel Bayrakdarian is an Armenian-Canadian operatic soprano acclaimed for her performances on international stages and her diverse repertoire spanning opera, concert, and recording projects.
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf6d74c8190a1d8d8fc24a06bd1 |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:38 p.m.