Triple
T6954554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prodigal Son |
E161208
|
entity |
| Predicate | leadActor |
P1507
|
FINISHED |
| Object | Keiko Agena |
E600880
|
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: Keiko Agena | Statement: [Prodigal Son, leadActor, Keiko Agena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Keiko Agena Context triple: [Prodigal Son, leadActor, Keiko Agena]
-
A.
Keiko Agena
chosen
Keiko Agena is an American actress best known for her role as the brainy and rebellious Lane Kim on the television series "Gilmore Girls."
-
B.
Mayuko Tanaka
Mayuko Tanaka is a Japanese public figure best known as the daughter of politician Makiko Tanaka and granddaughter of former Prime Minister Kakuei Tanaka.
-
C.
Yoshiko Satō
Yoshiko Satō is a Japanese individual notable enough to be recognized as a prominent bearer of the surname Satō.
-
D.
Sanae Takaichi
Sanae Takaichi is a Japanese conservative politician of the Liberal Democratic Party who has served in several ministerial posts and is known for her bids for party leadership and advocacy of hawkish security and traditionalist social policies.
-
E.
Yuko Tanaka
Yuko Tanaka is a Japanese academic and scholar who has served as president of Hosei University in Tokyo.
- 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dace1a94819095311e4288f01784 |
completed | March 27, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c75883f6888190a75515be49e7879e |
completed | March 28, 2026, 4:26 a.m. |
Created at: March 27, 2026, 2:29 p.m.