Triple
T11140424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katharina |
E263534
|
entity |
| Predicate | shortForm |
P43
|
FINISHED |
| Object | Kata |
E812678
|
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: Kata | Statement: [Katharina, shortForm, Kata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kata Context triple: [Katharina, shortForm, Kata]
-
A.
Kata
chosen
Kata is a common Hungarian feminine given name, typically used as a diminutive form of Katalin.
-
B.
Budo
"Budo" is a jazz composition featured on Miles Davis's influential album *Birth of the Cool*, known for its innovative arrangement and role in the development of cool jazz.
-
C.
Teppaku
Teppaku is a major railway museum in Saitama, Japan, showcasing the history, technology, and culture of rail transport through extensive exhibits and preserved trains.
-
D.
Maan Karate
Maan Karate is a 2014 Tamil-language romantic sports comedy film starring Sivakarthikeyan, known for its blend of fantasy elements, humor, and boxing-themed drama.
-
E.
Kenpō Kinenbi
Kenpō Kinenbi is a Japanese national holiday observed on May 3rd to commemorate the promulgation of Japan’s postwar constitution.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e860ca408190bea461e115f04fd7 |
completed | April 9, 2026, 5:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4420c17788190b72ca616fd5345f8 |
completed | April 19, 2026, 2:46 a.m. |
Created at: April 8, 2026, 9:28 p.m.