Triple
T9609578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke of Veragua |
E232062
|
entity |
| Predicate | notableFamilyName |
P18
|
FINISHED |
| Object | Colón |
E738667
|
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: Colón | Statement: [Duke of Veragua, notableFamilyName, Colón]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colón Context triple: [Duke of Veragua, notableFamilyName, Colón]
-
A.
Colón
Colón is a riverside city in Argentina known for its tourism, hot springs, and access to the Uruguay River.
-
B.
Colón
Colón is a major Panamanian port city on the Caribbean coast, known as a key gateway to the Panama Canal and an important center for trade and shipping.
-
C.
Colón
Colón is a municipality and city in western Cuba known for its agricultural surroundings and colonial-era architecture.
-
D.
Colón
Colón is a small municipality located in Colombia's southern Amazonian region within the Putumayo Department.
-
E.
Colón
chosen
Colón is a Spanish-origin surname commonly found in Hispanic communities and notably borne by figures such as comic book artist Ernie Colón.
- 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_69ca8485a90c819094fe40b42fde9d70 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a8469e081909c8fb7c84ffea2b3 |
completed | April 1, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18220a2308190aac7380c98f23965 |
completed | April 4, 2026, 9:26 p.m. |
Created at: March 30, 2026, 8:08 p.m.