Triple
T2016481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic of Genoa |
E44005
|
entity |
| Predicate | notableColony |
P160
|
FINISHED |
| Object | Caffa |
E67474
|
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: Caffa | Statement: [Republic of Genoa, notableColony, Caffa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caffa Context triple: [Republic of Genoa, notableColony, Caffa]
-
A.
Caffa
chosen
Caffa is the historical name of the Crimean port city now known as Feodosia, which was a major Genoese trading colony and a key Black Sea commercial hub in the Middle Ages.
-
B.
Sidamo
Sidamo is a Cushitic language spoken primarily in southern Ethiopia by the Sidama people.
-
C.
Berbera
Berbera is a major port city on the Gulf of Aden in Somaliland, serving as a key maritime hub for trade in the Horn of Africa.
-
D.
Mocha
Mocha is a popular JavaScript test framework used primarily for running unit and integration tests in Node.js and browser-based applications.
-
E.
Federico Caffè
Federico Caffè was an influential Italian economist and academic known for his work on welfare economics, Keynesian theory, and social justice in economic policy.
- 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_69a8891201bc8190aca837be6de41579 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb8ccdb7c81909f6b3c96f79fcdfc |
completed | March 7, 2026, 5:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0aef0fe88190adf9cd218cf7d8b4 |
completed | March 8, 2026, 11:49 p.m. |
Created at: March 4, 2026, 7:38 p.m.