Triple
T13239336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ter |
E315238
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Gironès |
E315236
|
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: Gironès | Statement: [Ter, flowsThrough, Gironès]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gironès Context triple: [Ter, flowsThrough, Gironès]
-
A.
Gironès
chosen
Gironès is a comarca (county) in the province of Girona, Catalonia, known for encompassing the city of Girona and its surrounding municipalities.
-
B.
Gironella
Gironella is a small municipality in Catalonia, Spain, known for its historic textile industry and location along the Llobregat River.
-
C.
Berguedà
Berguedà is a mountainous comarca in central Catalonia, Spain, known for its Pyrenean landscapes, rural villages, and natural parks.
-
D.
Cardedeu
Cardedeu is a municipality in the province of Barcelona, Catalonia, known for its modernist architecture and location near the Montseny Natural Park.
-
E.
Noguera Ribagorçana
Noguera Ribagorçana is a river in northeastern Spain that flows through the Pyrenees and Catalonia before joining the Ebro River.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d5850ac8190849a51da39efe5be |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff323a3c8190b46b24e69e653105 |
completed | May 3, 2026, 7:54 a.m. |
Created at: April 9, 2026, 9:23 p.m.