Triple
T16464367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phuket Big Buddha |
E399889
|
entity |
| Predicate | overlooks |
P1323
|
FINISHED |
| Object | Kata |
E1215297
|
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: [Phuket Big Buddha, overlooks, Kata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kata Context triple: [Phuket Big Buddha, overlooks, Kata]
-
A.
Kata
Kata is a common Hungarian feminine given name, typically used as a diminutive form of Katalin.
-
B.
Kata
chosen
Kata is a popular beach town on the southwest coast of Phuket, Thailand, known for its sandy shoreline, surfing, and relaxed resort atmosphere.
-
C.
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.
-
D.
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.
-
E.
Kata Wéber
Kata Wéber is a Hungarian screenwriter and playwright known for her emotionally intense collaborations with director Kornél Mundruczó, including the acclaimed drama "Pieces of a Woman."
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32d83687081908450657e1da6f6af |
completed | April 18, 2026, 7:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00581a11e881908681f68c26ee6a05 |
completed | May 10, 2026, 10:04 a.m. |
Created at: April 10, 2026, 5:10 a.m.