Triple
T648558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amerigo Vespucci |
E11294
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Amerigo |
E11294
|
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: Amerigo | Statement: [Amerigo Vespucci, givenName, Amerigo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amerigo Context triple: [Amerigo Vespucci, givenName, Amerigo]
-
A.
Amery
Amery is an English surname most notably associated with a British political family, including Conservative politician Julian Amery.
-
B.
Gama
Gama is a surname most famously associated with the Portuguese explorer Vasco da Gama, who pioneered the sea route from Europe to India.
-
C.
Amerigo Vespucci
chosen
Amerigo Vespucci was an Italian explorer and navigator whose voyages to the New World led to the continents of the Americas being named in his honor.
-
D.
Culebrita
Culebrita is a small, uninhabited cay off the coast of Culebra, Puerto Rico, known for its pristine beaches, clear waters, and historic lighthouse.
-
E.
Océan
Océan was a prominent French ship of the line that served as a flagship in major naval engagements during the age of sail.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f308f34819094ba28cfc786051e |
completed | March 1, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a58a716de88190854e13fb5143b9b3 |
completed | March 2, 2026, 1:02 p.m. |
Created at: March 1, 2026, 7:36 p.m.