Triple
T782081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Epirus |
E16518
|
entity |
| Predicate | containsPort |
P35
|
FINISHED |
| Object | Preveza |
E98737
|
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: Preveza | Statement: [Epirus, containsPort, Preveza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Preveza Context triple: [Epirus, containsPort, Preveza]
-
A.
Preveza
chosen
Preveza is a coastal city in northwestern Greece known for its strategic location at the entrance of the Ambracian Gulf, its historic old town, and nearby beaches.
-
B.
Morea
Morea was the medieval name for the Peloponnese peninsula in southern Greece, which served as a significant Byzantine province and later despotate.
-
C.
Otranto
Otranto is a historic coastal town in southern Italy’s Apulia region, known for its medieval castle, cathedral, and strategic position on the Adriatic Sea.
-
D.
Ragusa
Ragusa is a historic baroque hilltop city in southeastern Sicily, Italy, renowned for its UNESCO-listed old town and distinctive architecture.
-
E.
Quarracino
Quarracino is an Italian-origin surname most notably associated with Argentine Cardinal Antonio Quarracino.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a765ba688190ab328bb159583077 |
completed | March 1, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7a3afbb0c8190b4e7aa7824c8b787 |
completed | March 4, 2026, 3:14 a.m. |
Created at: March 1, 2026, 7:37 p.m.