Triple
T23221830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shō Tai |
E580914
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Shuri |
—
|
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: Shuri | Statement: [Shō Tai, placeOfBirth, Shuri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shuri Context triple: [Shō Tai, placeOfBirth, Shuri]
-
A.
Shuri
chosen
Shuri is a historic town on Okinawa Island best known as the former royal capital of the Ryukyu Kingdom and the site of Shuri Castle.
-
B.
Shuri
Shuri is a brilliant Wakandan princess and tech genius in the Marvel Cinematic Universe, known especially for her cutting-edge inventions and support of Black Panther.
-
C.
Keeya
Keeya is the wife of Leota Adebayo, a character in the DC television series "Peacemaker."
-
D.
Kiya
Kiya was a lesser-known wife of the Egyptian pharaoh Akhenaten, often associated with the Amarna period and subject to scholarly debate regarding her origins and role at court.
-
E.
Omi
Omi is the central protagonist of the 2015 Indian romantic drama film "Love," around whom the story’s emotional and narrative arc revolves.
- 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_69e2460389408190be74f41d217799a9 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1922924308190a26b00e09ce60ecd |
completed | April 29, 2026, 5:07 a.m. |
Created at: April 17, 2026, 4:08 p.m.