Triple
T22637573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Osuna |
E558721
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object | Osuna |
—
|
NE NERFINISHED |
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: Osuna | Statement: [House of Osuna, seat, Osuna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Osuna Context triple: [House of Osuna, seat, Osuna]
-
A.
Osuna
chosen
Osuna is a historic town in the province of Seville, Spain, known for its rich archaeological heritage, including notable ancient reliefs and other Roman-era remains.
-
B.
Senillosa
Senillosa is a small town in Argentina’s Neuquén Province, known for its agricultural activities and proximity to the city of Neuquén.
-
C.
Villarluengo
Villarluengo is a small rural municipality in the mountainous Maestrazgo comarca of the Aragon region in northeastern Spain.
-
D.
Cabrils
Cabrils is a small municipality in the Maresme comarca of Catalonia, Spain, known for its residential character and proximity to the Mediterranean coast.
-
E.
Adriasola
Adriasola is a Spanish-language surname, notably borne by Chilean lawyer and conservative political figure María Pía Adriasola.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1700edb608190ad786ff7fafea0da |
completed | April 29, 2026, 2:42 a.m. |
Created at: April 17, 2026, 3:03 p.m.