Triple
T11817918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cristóbal Colón de Toledo |
E281050
|
entity |
| Predicate | familyName |
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: [Cristóbal Colón de Toledo, familyName, Colón]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colón Context triple: [Cristóbal Colón de Toledo, familyName, Colón]
-
A.
Colón
Colón is a municipality and city in western Cuba known for its agricultural surroundings and colonial-era architecture.
-
B.
Colón
Colón is a riverside city in Argentina known for its tourism, hot springs, and access to the Uruguay River.
-
C.
Colón
Colón is a small municipality located in Colombia's southern Amazonian region within the Putumayo Department.
-
D.
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.
-
E.
Colón
Colón is a city in northeastern Honduras known as a regional hub near the Caribbean coast and the Bay Islands.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5e760988190b50d13bba5ef5b43 |
completed | April 10, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f16705cc888190b84537bd3cfbe1c2 |
completed | April 29, 2026, 2:03 a.m. |
Created at: April 8, 2026, 9:42 p.m.