Triple
T6891766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biscay |
E159064
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Gernika-Lumo |
E97708
|
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: Gernika-Lumo | Statement: [Biscay, contains, Gernika-Lumo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gernika-Lumo Context triple: [Biscay, contains, Gernika-Lumo]
-
A.
Gernika-Lumo
chosen
Gernika-Lumo is a historic town in the Basque Country of northern Spain, internationally known for the 1937 bombing that inspired Pablo Picasso’s famous painting "Guernica."
-
B.
de Garnica
De Garnica is a Spanish surname associated with individuals such as José de Garnica.
-
C.
Atocha
Atocha is a central Madrid neighborhood known for its major railway station, cultural institutions, and proximity to the city’s historic and museum districts.
-
D.
Aramburu
Aramburu is a Spanish-language surname of Basque origin borne by various notable figures in politics, religion, and sports.
-
E.
Prado
Prado is a neighborhood within the Brazilian city of Recife, known for its urban residential character and local commerce.
- 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_69c6883568c8819081db6407e892cccc |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d92ecbdc8190992f9c7f4f33f4c4 |
completed | March 27, 2026, 7:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c748d625908190b3b1f7cfe6360016 |
completed | March 28, 2026, 3:19 a.m. |
Created at: March 27, 2026, 2:24 p.m.