Triple
T1102895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Artemisa Province |
E25420
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Artemisa |
E127196
|
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: Artemisa | Statement: [Artemisa Province, hasCapital, Artemisa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Artemisa Context triple: [Artemisa Province, hasCapital, Artemisa]
-
A.
Artemisa
chosen
Artemisa is a Cuban city that serves as the administrative and economic center of Artemisa Province.
-
B.
Canazei
Canazei is a mountain village and ski resort in the Dolomites of northern Italy, known for winter sports and alpine tourism.
-
C.
Luna
Luna is the natural satellite of Earth, renowned for its phases, influence on tides, and prominence in human culture and mythology.
-
D.
Hesperia
Hesperia is one of the Hesperides, the nymphs of Greek mythology associated with tending a blissful garden at the western edge of the world.
-
E.
Theodosia
Theodosia is a historic port city on the southeastern coast of Crimea, known for its long history as a trading center on the Black Sea.
- 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9c375848190baec4d534f489616 |
completed | March 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac5391a4a88190b7ef6993b2b85b08 |
completed | March 7, 2026, 4:34 p.m. |
Created at: March 1, 2026, 7:43 p.m.