Triple
T10126923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Brühl |
E226237
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Colonia |
E408903
|
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: Colonia | Statement: [Daniel Brühl, notableWork, Colonia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colonia Context triple: [Daniel Brühl, notableWork, Colonia]
-
A.
Colonia
chosen
Colonia is the historical Latin name for the German city of Cologne, reflecting its origins as a Roman colony.
-
B.
Colonia
Colonia is the main administrative and population center of Yap State in the Federated States of Micronesia, located on the island of Yap.
-
C.
Colonia Doctores
Colonia Doctores is a traditional central neighborhood in Mexico City known for its historic streets, mixed residential and commercial character, and proximity to major civic and cultural institutions.
-
D.
Colonia Maza
Colonia Maza is a neighborhood in Mexico City located within the central borough of Cuauhtémoc.
-
E.
Colonia Narvarte
Colonia Narvarte is a centrally located residential and commercial neighborhood in Mexico City known for its mid-20th-century architecture, tree-lined streets, and vibrant urban life.
- 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_69ca843057b48190a86730167f5d6b98 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cdd2eef7388190b95ffd02814f2d1f |
completed | April 2, 2026, 2:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cc69a5c88190ab7b108e1aab20ba |
completed | April 5, 2026, 8:56 p.m. |
Created at: March 30, 2026, 9:05 p.m.