Triple
T17579295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujiwara no Teika |
E428156
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Teika |
—
|
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: Teika | Statement: [Fujiwara no Teika, givenName, Teika]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teika Context triple: [Fujiwara no Teika, givenName, Teika]
-
A.
Teika
chosen
Teika is the commonly used name for Fujiwara no Teika, a renowned Japanese poet, critic, and anthologist of the late Heian and early Kamakura periods.
-
B.
Kaku Tomeo
Kaku Tomeo was an Imperial Japanese Navy officer best known for commanding the aircraft carrier Hiryū during World War II, including at the Battle of Midway.
-
C.
Teio Sho
Teio Sho is a prominent Japanese horse race, contested by top-level thoroughbreds and held annually as a major event in the nation's racing calendar.
-
D.
Seishi
Seishi is a Japanese given name historically borne by figures such as Fujiwara no Seishi, a noblewoman of the Heian period.
-
E.
Tomoe
Tomoe is a central female character in the Japanese period drama film "The Twilight Samurai," known for her complex relationship with the protagonist and her role in challenging social norms of the era.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463cc493c8190965680cf786aa531 |
completed | April 19, 2026, 5:10 a.m. |
Created at: April 10, 2026, 5:50 a.m.