Triple
T3014667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catania |
E82307
|
entity |
| Predicate | ancientName |
P2834
|
FINISHED |
| Object | Katane |
E312784
|
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: Katane | Statement: [Catania, ancientName, Katane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katane Context triple: [Catania, ancientName, Katane]
-
A.
Katane
chosen
Katane is the ancient name of the city now known as Catania, located on the eastern coast of Sicily, Italy.
-
B.
Maskawa
Maskawa is a Japanese theoretical physicist best known for co-formulating the Cabibbo–Kobayashi–Maskawa (CKM) matrix, which explains quark mixing and CP violation in the Standard Model.
-
C.
Kyotanabe
Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
-
D.
Sachinomiya
Sachinomiya was the childhood name of Emperor Meiji, the Japanese monarch who oversaw the country's rapid modernization and the Meiji Restoration.
-
E.
Daikanyama
Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a69e8148190a97507740c9d26a8 |
completed | March 8, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12e6b78448190beb41460314278ec |
completed | March 11, 2026, 8:57 a.m. |
Created at: March 8, 2026, 3 p.m.